The awareness of scientists and policy makers regarding the requirement for an integrated One Health (OH) approach in responding to zoonoses has increased in recent years. However, there remains an overall inertia in relation to the implementation of practical cross-sector collaborations. Foodborne outbreaks of zoonotic diseases continue to affect the European population despite stringent regulations, evidencing the requirement for better ‘prevent, detect and response’ strategies. Response exercises play an essential role in the improvement of crisis management plans, providing the opportunity to test practical intervention methodologies in a controlled environment.Salmonella outbreak investigation at a national level, involving both the human food chain and the raw pet feed industry.The One Health European Joint Programme simulation exercise (OHEJP SimEx) aimed at practicing the OH capacity and interoperability across public health, animal health and food safety sectors in a challenging outbreak scenario. The OHEJP SimEx was delivered through a sequence of scripts covering the different stages of a A total of 255 participants from 11 European countries  took part in national level two-day exercises during 2022. National evaluations identified common recommendations to countries aiming to improve their OH structure to establish formal communication channels between sectors, implement a common data sharing platform, harmonize laboratory procedures, and reinforce inter-laboratory networks within countries. The large proportion of participants (94%) indicated significant interest in pursuing a OH approach and desire to work more closely with other sectors.The OHEJP SimEx outcomes will assist policy makers in implementing a harmonized approach to cross-sector health-related topics, by highlighting the benefits of cooperation, identifying gaps in the current strategies and suggesting actions required to better address foodborne outbreaks. Furthermore, we summarize recommendations for future OH simulation exercises, which are essential to continually test, challenge and improve national OH strategies. Therefore, fostering cross-sector collaboration and disease response preparedness under the framework of One Health (OH) has become a priority for many countries . The awaWhile the theoretical aspects of OH have been well established and embraced within the scientific community, practical implementation has been hindered due to the complex requirement of political, ethical, economical, and societal engagement , renderiSalmonella enterica serotype Typhimurium in several food categories, it remains as an important gastrointestinal pathogen in EU, accountable for 22% of all foodborne outbreaks in 2020  to more complex operation-based exercises . Table-top exercises are a common format for simulation exercises, offering the opportunity to be completed in an informal and stress-free environment where the participants are guided by a facilitator and encouraged to engage in a roundtable discussion based on a simulated scenario. A series of scripted injects are given to the participants, presenting the problems that need to be tackled. This type of exercise stimulates the participants’ problem-solving capacities and develops the communication strategies required to respond effectively in the event of an actual disease incursion. Although table-top exercises lack the full realism of functional or full-scale exercises, they provide an effective and efficient way to become familiar with procedures and policy. Moreover, this format is not necessarily timebound, therefore allowing the participants to allocate time to focus on the critical elements of the scenario –18.Salmonella outbreak scenario was developed, which included both human food and pet feed supplies specifically to provide the opportunity to share experiences and perspectives across sectors, evidencing the added value of applying a OH approach, while also providing an opportunity to test a food tracing software tool: The FoodChain-Lab (FCL) web application. By assisting countries to identify current gaps in their OH approach to a foodborne outbreak and defining strategies to tackle them, the OHEJP SimEx outcomes have resulted in recommendations suitable for all countries to assist in defining a national roadmap for future outbreak preparedness plans.Within the remit of the One Health EJP, the multi-country OHEJP SimEx was designed with an overall aim to practice the OH capability, capacity, and interoperability at a national level, across public health (PH), animal health (AH) and food safety (FS) sectors. To succeed in this aim, a challenging outbreak scenario with a zoonotic disease that typifies the OH concept and that was relevant across Europe was required. Therefore, a 2.2.1.Within the One Health EJP, a Joint Integrative Project (JIP) priority topic was identified: “Sharing best intervention practice – twinning and simulation exercises.” To address this topic, the OHEJP SimEx project was designed. A OHEJP SimEx Steering Board was formed with representatives from the One Health EJP Project Management Team. The Steering Board provided the Project Directive. Relevant stakeholders, European Centre for Disease Prevention and Control (ECDC), European Food Safety Authority (EFSA), Food and Agriculture Organization of the United Nations (FAO), World Organisation for Animal Health (WOAH) and World Health Organization (WHO) were represented in an Advisory Board. The timeline for the project was constrained within the overall OHEJP project timeframe. Preparation for the project began in January 2021 with the appointment of a project leader and included recruitment of an international project team of nine specialists with complementary expertise in the areas of PH, AH and FS and emergency response exercises. The team was responsible for planning, supporting the national conductions, evaluating the outcome of OHEJP SimEx and dissemination of the outcomes which began in September 2021 and completed in December 2022 . MeetingThe OHEJP SimEx project team developed a realistic scenario which could be executed in multiple European countries including the following criteria:The pathogen must be relevant across EuropeThe pathogen must satisfy the One-Health focus spanning AH, PH and FSCountry level focusCross sectoral collaboration focusData sharing focusThis exercise was included as an implementation activity in One Health EJP. All One Health EJP partner institutes were invited to participate in the OHEJP SimEx. In addition, the institutes were encouraged to invite other institutes from outside the One Health EJP consortium, e.g., to cover up for missing sectors or to better represent the national outbreak management. Participation of institutes was on a voluntary basis. The original request and subsequent reminders to participate in the exercise were sent out by email to the following groups within the One Health EJP: Scientific Steering Board members, representatives from the Programme Managers’ Committee and Project Leaders. All partners that decided to participate selected a contact person who become the link between the institute and the One Health SimEx Project Team. The contact person from each institute was then fully involved in the decision-making process about participation. In November 2021, 15 countries had expressed their willingness to participate in the exercise. By the time of the preparatory workshop (see Section 2.3) for the National Exercise Leaders (NELs) and Local Exercise Leaders (LELs) in March 2022, two countries had decided to withdraw due to their national outbreak teams being heavily involved in the COVID-19 pandemic and avian influenza outbreak responses. A further two countries withdrew due to difficulties in involving all sectors and changes in leadership, respectively. Thus, conduction of the scenario involved eleven countries .Then, in order to conduct the exercise at national level, it was necessary for each participating country to assemble a national team, including representatives from PH, AH and FS. Each national team was composed of a NEL, LELs, Local Evaluators (LEs), and a Training Audience (TA) . Each paThe OHEJP SimEx was designed as a table-top exercise in which the participants were encouraged to meet in person for the conduction. Final decisions regarding organization of the conduction were made by the national teams. The OHEJP SimEx ran for 2 days and was conducted in the participating countries during the period of May to September 2022.2.2.Salmonella enterica serotype Typhimurium outbreak at a national level involving both the human food chain and the raw pet feed industry. To ensure that a cohesive language was used between sectors, the OH glossary produced within the One Health EJP was used , EFSA, One Health EJP COHESIVE and other European projects, which allows to model, visualize, and analyze complex food supply chain networks , 22. ThiA final meeting at the end of the exercise allowed the TA to review and discuss the challenges encountered during the simulated outbreak investigation and management.2.3.The OHJEP SimEx evaluation was designed to assess the success of the objectives to identify any limitations on data sharing, develop intersectoral communication strategies and increase the mutual understanding between sectors. By identifying cooperation gaps, the evaluation also provided evidence to support the improvement of future foodborne outbreak management strategies with a OH approach.The LEs attended a training session, delivered by the OHEJP SimEx project team prior to conduction to prepare and support them. This included how to conduct After-Action Review . The guided AAR discussions covered the chronological narrative of the conduction, focusing on the most relevant decisions to highlight the strengths and weaknesses identified. Hot debriefs provided participants with the vital opportunity to share their thoughts while the experience is still fresh, avoiding missing relevant details. Post-conduction, a link to a survey was sent to all participants , to provide the project team with invaluable feedback on their experiences. To guarantee representative value, a minimum response rate of 80% was aimed for. The majority of questions were posed according to the Likert scale with four different options: strongly disagree, disagree, agree, strongly agree. To facilitate the interpretation of the feedback, these options were reduced into two categories: disagree and agree. Answers were processed in Microsoft Excel  and presented as descriptive statistics.The LEL of each institute was responsible for analyzing its own outcomes which were combined by the NEL to deliver a national report covering the experiences of the conduction, main lessons learned and recommendations for future improvement. The OHEJP SimEx project team provided a template for the national report to ensure a level of consistency in the information provided. The OHEJP SimEx project team analyzed the national reports to identify common problems, major gaps, and current best practices. However, because the report template did not explicitly request answers to a series of questions, the data presented below was compiled from the information provided and may not represent a complete picture.By compiling and analyzing data from all the evaluation outcomes, we have provided a comprehensive analysis and summarized a list of recommendations for the improvement of OH approach to foodborne outbreaks as well as suggestions for future OH simulation exercises. In addition, the national experiences were shared at an internal One Health EJP Scientific Steering Board meeting (28th of September 2022) and at a dedicated Joint SimEx/Dissemination Workshop ‘A One Health simulation exercise as a roadmap for future foodborne outbreak preparedness’ (6th December 2022) that was targeted to stakeholders.2.4.via an electronic questionnaire in EUSurvey  with Amendment #1–2020. This consortium agreement is based upon regulation (EU) No 1290/2013 of the European Parliament and of the Council of 11 December 2013 laying down the rules for the participation and dissemination in “Horizon 2020 – the Framework Programme for Research and Innovation (2014–2020).” The data in the post-exercise survey, completed by the participants, were collected EUSurvey  set in a3.n = 205), confirming that the results can be considered representative.In total, 255 participants from 42 institutions from 11 countries  completed the OHEJP SimEx , from whn = 47) of participants belonging to the AH sector, 35% (n = 71) to the FS sector and 37% (n = 75) to the PH sector. Twelve participants (6%) did not identify with a sector. The overall opinion on the exercise was positive, with 94% (n = 192) of participants reporting feeling encouraged to pursue a OH approach by working more closely with other sectors in future outbreak situations.Based on the post-conduction survey results, there was a balanced representation across the three sectors, with 23% (3.1.n = 195) and chosen pathogen (n = 201) relevant, 89% (n = 183) expressed that the scenario equally covered all the sectors, and 95% (n = 194) considered the scenario was in line with the exercise objectives. Sixteen percent (n = 32) of participants reported a lack of reality in the way the outbreak unfolded and 26% (n = 54) of participants did not think the injects fully mimicked a real-life outbreak situation.The majority of the participating countries decided that the scenario was suitable to utilize as provided. However, minor adaptations were made by four out of the 11 countries. Modifications included adding information to explore topics of national relevance or providing supporting documents to the TA. In addition, one country made more significant changes to the scenario to replicate the structure of their national system. Four countries chose to translate the documents into a local language prior to conduction. Over 95% of participants reported finding the scenario  that experienced changes in the TA members during the exercise conduction, hindering continuity from 1 day to the next.Organization of the facilities during conduction varied amongst the participating countries. Using one large room and seating the TA according to sector was reported as beneficial by resembling the reality of interinstitutional collaboration. The majority of countries either used a single large table or separated the TA around smaller tables by sector whilst ensuring intersectoral communication was still possible. The LEs mostly assumed a position separated from the TA. Five countries opted to conduct the OHEJP SimEx online. The importance of having a cohesive TA from the beginning to the end was evidenced by the problems reported by countries (n = 197) and venue (n = 191) logistics and 98% (n = 201) expressing their satisfaction with the performance of the NELs and LELs. The time frame for the sequence of events and the discussion time allocated to each inject worked well for the majority of countries, of those that did not agree included that the time frame did not resemble the country’s reality and that not enough time was allowed for discussion.The post-conduction survey results noted positive feedback on the exercise organization, with over 94% of all participants either agreeing or strongly agreeing with aspects related with the time , considering it useful for the exercise and some even requesting a more extensive practical exercise. Participants not directly involved in outbreak investigations and tracing, e.g., the communication experts, were less integrated in this part of the exercise.Inclusion of FCL in the exercise was considered an opportunity for participants from AH and PH to better understand FS tracing procedures. The overall opinion on FCL varied, with most, 93% , stated the exercise was successful in highlighting the role of each sector in an event of a foodborne outbreak, and in showcasing the functionality of the systems in place (85% (n = 174) agreement)  . Five coThree countries noted that an outbreak management team is only assembled once an outbreak has been declared, resulting in a fragmented decision-making process in the absence of a cohesive multidisciplinary team. One country reported that they have a long-standing collaboration for outbreak investigations and management.Several countries highlighted the role of OHEJP SimEx in bringing people together and helping to strengthen interpersonal relations between professionals across sectors. In particular in the countries where the sector organization was more dispersed, OHEJP SimEx provided a unique opportunity for people to meet and clarify their roles. Moving toward or strengthening a single cooperating food safety governance structure, including both the human food chain and animal feed seemed to be the preferred system.The need for further training initiatives covering institutes at different hierarchical levels to promote a common understanding between all parties involved and a quicker implementation of the necessary legal actions  was highlighted in several country reports. Four countries mentioned the key role of National Reference Laboratories in bridging the gaps between the different sectors and authorities, revealing the advantages of including them in the training initiatives.One gap highlighted by four countries was that most interinstitutional communication was based on personal contacts and established through informal communication routes. The advantages of contacting professionals from other sectors using a personal contact network are largely recognized as a quick and efficient communication method, but a dependence on private networks is vulnerable particularly when there is a change in personnel.Although not specifically focused on as it is outside the remit of a national response, it was evident that most countries had excellent knowledge and functionality of international early warning systems, e.g., the EpiPulse ECDC tool , which a3.3.n = 184) of the participants reported to have improved their understanding of the importance of data harmonization practices after conduction, 18% (n = 36) indicated that their institute did not prioritize the implementation of such practices (n = 8) reported a requirement for an interinstitutional data sharing and data collection platform accessible to all sectors. Fragmented data collection structures, designed and implemented at an institute level, were considered to result in incompatible outputs and/or restrictive sharing policies, and proved inadequate for the OH scenario explored in this exercise.The second part of the scenario focused on harmonized approaches to data collection. The results showed that the OHEJP SimEx allowed different sectors to explore their data sharing procedures and to identify possible gaps that may hinder a coordinated and common data management plan. While 90%  that applies to different data. The participants raised legal questions on data accessibility, under which circumstances they can be accessed, and for what they can be used. Most participants also noted a need for clearer guidelines on GDPR in relation to pathogen isolates and microbial genomic information. Other challenges identified by the participants included the lack of political will, the absence of harmonized data collection methodologies and the need for further training in data analysis, particularly in the area of whole genome sequencing (WGS).3.4.n = 189) expressed having increased their understanding of communicational needs and target audience identification , and the inclusion of raw pet food in the exercise. The latter was not yet a relevant market in some of the participating countries, therefore the structures and regulations relating to raw pet food were not well defined. Rather than view this as a disadvantage, the experience for the TA in these countries is uniquely placed to assess the issues and successes each country encountered and provide recommendations for future One Health initiatives. If designing a more detailed exercise, it might be useful to identify countries with a similar prevalence for the selected pathogen and similar relevant systems , allowing more detailed analysis into specific areas. If countries wish to participate without this alignment, then excluding them from the analysis, or separating countries according to how well they align to the pre-requisites will enable them to benefit from the exercise and provide some important data without affecting the main aims of the exercise. It is important to have a strong representation of all the different OH sectors in the exercise planning team to avoid a biased representation of a specific sector over the others, thus guaranteeing that the exercise can explore relevant topics for each sector.To align with the local conditions, the participating countries were given the option to adapt the scenario. Despite this, there were some conflicting opinions from the TA on the exercise content and delivery. Indeed, the variations in via the environment or for novel pathogens where limited knowledge exists and be encompassed in future simulation exercises. Furthermore, in one of the countries unable to secure representation from all three sectors, the TA noted more dissatisfaction regarding the relevance of the scenario, as they could not fully engage in all the injects, an observation that stresses the importance of including all sectors represented in the scenario. Although communication was central to this scenario, an even stronger focus on communication is recommended for future simulation exercises. Indeed, participants identified in some countries the communication staff only had a secondary role during the majority of the OHEJP SimEx. Including from the onset communication experts within the exercise planning team could address this concern. Incorporating more practical tasks  should also be considered to increase the overall participation and engagement.By including the environmental health sector, future exercises could explore additional aspects of this from a OH perspective often-overlooked sector. When building the scenario, environmental pathogen dissemination was not included as a key event to explore in this exercise, but we noticed that the topic arose during some team discussions and that the absence of environmental health professionals in the TA hindered the development of such discussions. Therefore, the environmental health sector should be considered as an essential part of the holistic OH approach for pathogens that are known to transmit Based on the weaknesses and strengths identified amongst the different countries it is possible to note common topics requiring improvement to implement the OH strategy to outbreak investigation and management. Countries should strive to set up a OH coordination strategy before a specific need for it is identified, ensuring a well-established organization able to support a prompt and efficient response . InterinEstablishing a routine of meetings with representatives from the different sectors should be considered a priority for countries aiming to improve their OH strategy. Meeting regularly builds trust and promotes transparency between and within sectors, which is fundamental for a successful cross-sectoral cooperation. To develop an efficient health emergency response system which is capable of quickly adapting to different scenarios, all relevant sectors must be identified and equitably included. Ideally, to enable a swifter decision-making process, at least one member of each sector should have a direct link to governmental bodies to facilitate the communication with policy makers when needed , 27. TheThe successful implementation of OH structures requires a good understanding of the national and regional context and priorities . ImplemeIt was noteworthy that almost all participating institutes declared a dependance on personal and informal communication routes, which compromises the sustainability of interinstitutional communication networks. An effort should be made to implement efficient and official structural communicational channels that can be sustained regardless of personal contacts. These should include contact points at several key organizations, be regularly updated and be easily accessible to all relevant parties while still avoiding complex instructions that diminish compliance.By centralizing the typing data of pathogen strains from different sources, the data can be made available to the investigation team without delays, helping to move forward with the outbreak investigation. Fragmentation of laboratory services can be time and resource consuming, hinder the harmonization of the results and increase the risk of information delays in the communication between laboratories. When centralization is not feasible or preferred, an effort should be made toward the harmonization of the characterization methods used in the different laboratories so that the results can be transferable and comparable . To suppThe need for a common data sharing platform that can be used across sectors was a common outcome across the participating countries and its implementation is pivotal in achieving a OH approach. Efficient tools are needed for earlier identification of outbreaks and quicker access to data for analytical studies and source attribution. Ideally, new data sharing platforms should build from and integrate already existing databases, be able to support large amounts of data and allow for multiple users to access simultaneously. To assist in the transition to an integrated strategy, institutes could develop guidelines on interinstitutional data sharing practices. Harmonization efforts could start at an institutional level by promoting a standardized use of internal data management tools by the professionals to avoid the vulnerability of a system dependent on a limited number of people. Ideally, national surveillance systems would be standardized internationally, thereby facilitating a coordinated approach to cross-border foodborne outbreaks.It was noteworthy that GDPR was highlighted as a major barrier to the implementation of shared data collection across sectors. All personnel with access to the data related to an outbreak will need to be aware of, and comply with, the GDPR that applies to the different data categories and be authorized to work with it. Based on the comments from the participating countries, restricting access to common data sharing platforms to the central authority of each sector was considered preferential. Nevertheless, an efficient communication route needs to be established with the authorities at a regional level to guarantee the quick and efficient implementation of any actions that may be required.Outbreak investigations comprise of both epidemiological and pathogen-related data. The majority of recommendations and gaps identified were concerning epidemiological data. However, it is important to raise awareness regarding inclusion of pathogen data, in particular genomic data, in national data sharing plans, which are used for cluster identification and source attribution. Ideally, national databases that connect AH, PH and FS laboratories should be created in countries that lack these databases and extended to include more pathogens in countries that already have them in place. To ensure genomic data is used optimally, the protocols used to generate the data and output formats need to be standardized across the different laboratories prior to implementation. As the demand for better and quicker typing techniques increases, there is a need to invest in WGS technologies and building the capacity of skilled teams that can generate and analyze large amounts of genomic data in real time.Data visualization tools like the FCL, can prove helpful during an outbreak situation by allowing to visualize and analyze complex food networks, help in data collection, tracing back analysis and source attribution. Nevertheless, some points were raised regarding the complicated and time-consuming process of entering data into the FCL platform, and that it may be hard to adapt the tool to a more complex OH incident where the data is too heterogeneous. For the optimal implementation of the tool, it is necessary to improve its interoperability with other information systems and databases (possibly including sequencing data) and offer training on how to use the platform. Countries that showed interest in implementing FCL in their national action plan for foodborne outbreak investigations were given the opportunity to attend a workshop with the tool designers to help with the process. Future multi-country simulation exercises should take the opportunity to include different practical tools such as FCL as it provides a unique platform to fully test the complexities of country specific requirements. Providing a more robust range of suggested improvements benefitting future users.As noted by many of the countries, the inclusion of communication experts from the different sectors in the outbreak management team is essential to ensure the public perception on the cohesiveness of the team and to promote internal mutual understanding. To assure consistency, their inclusion should precede the assembly of the emergency team and considered in the early construction of OH mechanisms . It is iThe One Health EJP is composed of public institutes in the AH, PH and FS sectors and therefore has close collaboration with national and international stakeholders, including those represented in the OHEJP SimEx Advisory Board. This collaboration has enabled sharing the experiences from OHEJP SimEx to policy makers, whose support is essential for establishing and strengthening the structures needed to implement a OH approach to investigation and management of outbreaks. For the successful implementation of the actions identified here, they need to be assessed taking into consideration each national reality and adapted accordingly. There are several tools and resources available to support decision makers in making the transition to better OH structures and support them in drawing national action plans that can address the major gaps .5.The OHEJP SimEx was a successful multi-country national simulation exercise. The results revealed the need for initiatives that can support countries in the practical implementation of OH. With the persistent risk of zoonotic foodborne outbreaks there is a continuous need to invest in prevention and contingency, as well as building capacity to respond to a health emergency, using an OH approach. Future OH simulation exercises can build on the OHEJP SimEx structure and experiences and should try to address the limitations identified. All participants acknowledged the essential tasks to engage with stakeholders and policy makers in order to ensure the framework of practical implementation of a OH approach is supported.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.AO and KA conceptualized the project. AB, AO, DM, FA, JB, LT, ML, OP, and RF contributed to scenario design and development, evaluation, and reporting and dissemination of results. AB, AO, DM, FA, JB, LT, ML, OP, PJ, and RF contributed to data collection. OP analyzed the survey data. AO and FA drafted the manuscript. DM contributed to communication, information sharing, and language editing. HI, KA, PJ, and RR contributed to the project design and editing and writing the manuscript. All authors contributed to the article and approved the submitted version.The project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No. 773830.The authors declare that the OHEJP SimEx project was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Background: Fatty liver disease (FLD) is an important risk factor for liver cancer and cardiovascular disease and can lead to significant social and economic burden. However, there is currently no nationwide epidemiological survey for FLD in China, making early FLD screening crucial for the Chinese population. Unfortunately, liver biopsy and abdominal ultrasound, the preferred methods for FLD diagnosis, are not practical for primary medical institutions. Therefore, the aim of this study was to develop machine learning (ML) models for screening individuals at high risk of FLD, and to provide a new perspective on early FLD diagnosis. Methods: This study included a total of 30,574 individuals between the ages of 18 and 70 who completed abdominal ultrasound and the related clinical examinations. Among them, 3474 individuals were diagnosed with FLD by abdominal ultrasound. We used 11 indicators to build eight classification models to predict FLD. The model prediction ability was evaluated by the area under the curve, sensitivity, specificity, positive predictive value, negative predictive value, and kappa value. Feature importance analysis was assessed by Shapley value or root mean square error loss after permutations. Results: Among the eight ML models, the prediction accuracy of the extreme gradient boosting (XGBoost) model was highest at 89.77%. By feature importance analysis, we found that the body mass index, triglyceride, and alanine aminotransferase play important roles in FLD prediction. Conclusion: XGBoost improves the efficiency and cost of large-scale FLD screening. Fatty liver disease (FLD), a global epidemic disease, is an important risk factor for liver cancer ,2. HowevAs a prediction tool, machine learning (ML) represents the latest development of statistics. Unlike the traditional statistical model, which depends on certain assumptions for data and a clear mathematical form, ML does not have any assumptions about the data, and the results eliminate the classical statistical framework based on hypothesis testing. The prediction efficiency of ML models based on algorithms or programs is high, and the results of cross-validation are easy to understand, so ML can be widely used in medical diagnosis trials today. Among them, several ML methods, such as random forest (RF), artificial neural network (ANN), K-nearest neighbor (KNN), and support vector machine (SVM) have played an important role in the prediction of many diseases.Previous studies  have extBased on in-depth ML approaches to diagnosing FLD, there are many artificial methods that can diagnose fatty liver with high accuracy. However, most of these diagnoses are based on abdominal ultrasound or computed tomography (CT) images, which are costly for fatty liver screening. Compared with the image-based ML screening methods, using physical examination data and blood biochemical indexes as predictive indicators can screen fatty liver in an efficient and economical way. Thus, the main purpose of this study was to build an efficient and robust FLD screening ML model based on these indicators.The dataset used in this study was provided by the health management center of the Second Xiangya Hospital of Central South University, Changsha, China, and included the data of 36,527 patients. We enrolled individuals aged 18–70 years from January 2013 to December 2019. During the process of data collection, no privacy information was included. Only 23 indexes, including physical examination data, age, and blood biochemistry indexes were included. Because ML models rely on data integrity, 4908 individuals with missing values of more than 30% were excluded, and the remaining missing values were completed by the multiple interpolation method. In this study, the diagnosis of FLD was based on the results of abdominal ultrasound images. The ultrasound machines used in this study were the Philips Medical Systems model iU22 and model Epiq . All the diagnostic results of abdominal ultrasounds were performed by attending physicians in our hospital’s imaging center and were reviewed by senior physicians. The diagnostic criteria for FLD were based on the guidelines published by the Chinese Medical Association in 2010 . The diaIn machine learning data preprocessing, class imbalance is a common issue where the number of samples in one category is much larger than in the other. This can present challenges for machine learning models, and the severity of the imbalance depends on the proportion of samples in each category. To address this problem, this study used a synthetic minority over-sampling technique nominal continuous (SMOTE-NC)  to handlFeature selection is a crucial aspect of classification tasks, as it can significantly impact the performance of the model. The main objective of feature selection is to identify the most relevant subset of features that can improve the accuracy of classification. In the context of the 11 characteristic variables presented in We used the createDataPartition function in the caret package to divide the training set and the test set, in which the test set accounted for 70% of all data. Continuous variables were normalized by subtracting the average value and dividing by the standard deviation. To overcome the imbalance problem in the training set, we used the synthetic minority oversampling technique to randomly generate new individuals of the minority, which have similar features to the original individuals of the minority class. We used the eight most common classifiers to build an FLD screening model. As one of the most commonly used generalized linear regression models for binary data, logistic regression (LR) can not only provide prediction results, but also indicate the weight of each independent variable in the prediction. RF is a classifier that integrates multiple decision trees. All decision trees are independent of each other, and each decision tree splits the maximum information gain, and finally outputs the results of classification after reaching the threshold; the RF results are based on the majority of all decision trees. As a common two-classification model, the SVM maps the feature vector to the space, and finds the separation hyperplane with the largest interval in the feature space. This approach makes the classification results more robust and improves the generalization ability of the model. Linear discriminant analysis (LDA) is a classical supervised learning method based on data dimensionality reduction, which classifies the data by projecting the data from a high-dimensional space to a lower-dimensional space and ensuring that the intra-class variance of each class is small and that the mean difference between classes is large. Quantitative descriptive analysis (QDA) is a variant of LDA that allows the nonlinear separation of data. KNN is regarded as a nonparametric, lazy algorithm model that is based on adjacent samples with the minimum Euclidean distance. This model makes no assumptions about the data, and there is no clear training data process. Because it assigns the same weight to different features, the model is easily affected by noise. Extreme gradient boosting (XGBoost) is an improved boosting algorithm based on the gradient boosted decision tree (GBDT) method. Unlike with classical GBDT, second-order Taylor expansion is used in XGBoost on the error part of the loss function, which improves the accuracy of the loss function definition. Because of the L2 regularization in the cost function, the complexity of the XGBoost model is controlled, which greatly reduces the possibility of overfitting. Because of these characteristics, XGBoost has excellent classification and regression prediction performance. An artificial neural network (ANN) is a black box model constructed by simulating the brain’s neural structure, and is generally composed of an input layer, hidden layer, and output layer. Each layer may contain multiple neurons. The number of neurons in the input layer depends on the input parameters, and the number of neurons in the other layers is adjusted according to the actual situation. In this model, the input parameters are connected to the neuron on the basis of a certain weight. The activation threshold of the neuron is determined by setting the activation function; then, the signal is further transmitted in the network. The neural network can achieve self-learning through forward propagation or back propagation, and gradually optimizing the weights and deviation values in the process until the value of the loss function tends to be stable and reaches the expected value. Finally, the network generates the results through the output layer. In this study, all the parameters in the models were adjusted by cyclic traversal, and the highest area under the curve (AUC) value was regarded as the selection standard of the model parameters . A 10-foWe verified the predictive ability of the ML model by calculating the area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and kappa value. In this section, we provide an overview of the various metrics used to evaluate the performance of machine learning models.TP, TN, FP, and FN represent true positive, true negative, false positive, and false negative, respectively.Accuracy is a crucial evaluation metric in machine learning and represents the proportion of correctly predicted samples in the overall sample. A higher accuracy indicates better classification performance. The formula used for calculating accuracy is as follows:Sensitivity, as known by the true positive rate, is a critical performance metric for machine learning models, as it quantifies the model’s ability to accurately identify patients who test positive. It measures the proportion of actual positive cases that the model correctly identifies as positive, providing insight into the model’s ability to detect true positives.Specificity refers to the proportion of negative cases identified out of all negative cases. It is a measure of the ability of a machine learning model to correctly identify negative cases. The higher the specificity, the lower the false positive rate, and the more accurate the model’s negative predictions.Positive predictive value (PPV) is a performance metric in machine learning that measures the proportion of true positive predictions made by the model among all positive predictions. In other words, PPV represents the probability that a positive prediction is actually correct.Negative predictive value (NPV) is another performance metric in machine learning that measures the proportion of true negative predictions made by the model among all negative predictions. NPV represents the probability that a negative prediction is actually correct.oP is the observed proportion of agreement between the two classifiers, and eP is the expected proportion of agreement due to chance.Kappa is a statistical measure of agreement that takes values between −1 and 1. In the context of the classification problem under study, it indicates the degree of agreement between the model’s predicted results and the actual classification results. As a rule of thumb, a higher kappa value is often regarded as indicative of stronger agreement between the classifier and the actual results.Receiver operating characteristic (ROC) curves are a graphical representation of the performance of a binary classifier system. The ROC curve is created by plotting the true positive rate (TPR) against the false positive rate (FPR) at various threshold settings. A perfect classifier has an ROC curve that passes through the top left corner of the plot, indicating a high TPR and low FPR. AUC is a measure of the classifier’s ability to distinguish between positive and negative classes, with an AUC of 1.0 indicating perfect classification and an AUC of 0.5 indicating random guessing.The Shapley value is a concept from cooperative game theory that measures the marginal contribution of each player to a cooperative game. For machine learning, the Shapley value represents the contribution of a feature to a prediction by considering all possible combinations of features that could have been used in the model. It measures the average change in the model’s output when a feature is added, compared to when the feature is not included. The Shapley value can help identify the most important features for a particular prediction and to understand how the model makes decisions. While the SHAP library’s kernel Explainer is capable of computing Shapley values for any machine learning model, it is computationally inefficient for KNN models. Although the k-means clustering algorithm can be used to summarize the data and improve computational efficiency, this comes at the expense of the model’s accuracy. To address this, we evaluated the feature importance of the KNN model using root mean square error loss after permutation in this study.t-test showed a significant difference between the two groups , and the two-sample o groups . The denThe ROC curves for all models are shown in This study included the clinical data of 30,572 subjects and 8 ML models, which makes it by far the largest machine learning study based on physical examination and blood biochemical indicators to predict fatty liver in the Chinese population. According to the results, it is not difficult to find that ML can efficiently predict the occurrence of FLD, and the XGBoost model is the best predictor among all the analyzed models. This is likely due to the XGBoost model’s ability to adaptively adjust the depth of trees and weights of leaf nodes to minimize the loss function, as well as mitigate overfitting issues by incorporating regularization terms. The XGBoost model can handle datasets with a large number of features and samples, and identify key factors through feature importance evaluation, thereby improving the model’s interpretability and reliability. These advantages make the XGBoost model highly accurate in binary classification predictions and perform exceptionally well in the diagnosis of many clinical conditions ,16,17. PMoreover, on the basis of the decision tree model, we constructed a simplified screening model  for physThe traditional diagnosis of fatty liver mainly depends on imaging results or invasive biopsies, which have high medical and human resource requirements. However, the predictive index of FLD screening based on machine learning is easier to obtain, and the results do not rely on the subjective judgments of doctors. The dataset used for predicting fatty liver disease is mainly unbalanced and categorical, with a much lower number of patients with fatty liver disease than those without. This study utilized the SMOTE-NC method to preprocess the unbalanced data and applied the AIC backward propagation technique for feature engineering. As a result, our model achieved an accuracy comparable to that of a previous study while using fewer feature variables ,26, inclThis study had some limitations. First, although more than 30,000 samples were included in this study, these samples were all from the Second Xiangya Hospital of Central South University, and the population representation was less comprehensive than that of multi-center clinical studies. The generalization ability of the model in different ethnic groups is open to question. Second, the response variables used in the machine learning model constructed in this study are solely based on the diagnostic results of abdominal ultrasound, which have a lower level of evidence compared to liver biopsy and magnetic resonance imaging (MRI). This may potentially affect the accuracy of the predictions. Thirdly, tumor, hepatitis, and other metabolic diseases  were not excluded from the population included in this study. As a result, the potential impact of these factors on the predictive model could not be fully assessed. Lastly, it should be noted that we did not gather data on alcohol consumption and medication history among the study population. Therefore, we were unable to rule out the potential interference caused by alcohol and drugs. Previous studies have indicated that both factors can influence the development of fatty liver ,30,31. TIn this study, we found that ML models, especially XGBoost, can predict FLD through demographic indicators, blood glucose, liver function test, and blood lipid profile with high accuracy and good repeatability. Among 11 predictive indicators, BMI, Alt, and Tg are vitally important for most models. With the aid of these machine learning methods, physicians can now evaluate a patient’s fatty liver condition in its incipient stages, even in the absence of liver biopsy or imaging evidence. This early assessment can facilitate timely diagnosis and provide a novel avenue for the early screening of fatty liver in primary healthcare facilities. In future research, we will collect more data from various populations to further modify the model and give it better generalization ability.


This article was migrated. The article was marked as recommended.Healthcare education is complex and multifaceted, requiring study from different angles and with different lenses. We propose that the use of a meta-framework can help those teaching and researching postgraduate health professions education make holistic sense of their practice and findings from different projects. We discuss how we have employed Bronfenbrenner’s ecological systems theory (EST) as an overarching theoretical framework for the scholarship of learning and teaching in the context of postgraduate health professions education. Taking a structured approach to pedagogical thinking and research through the use of a meta-framework opens up useful ways of framing findings and further questions, locating research projects within a bigger picture, and communicating to others the focus of a research programme. We address the problem of the under-theorizing of educational research in postgraduate health professions education, advocating both theoretical frameworks for individual research projects, and an overarching theoretical “meta-framework” to interrogate and draw together multiple studies. In doing so we build on, critique and further develop Bronfenbrenner’s ecological systems theory. Recent years have seen a rapid expansion of postgraduate taught (PGT) programmes designed to enhance health professions education (HPE); many (including our own) are delivered online. The provision of continuing education for healthcare professionals is big business, as attested by the proliferation in the number of PGT-HPE courses offered worldwide, currently estimated at over 100 . One insPGT-HPE programmes are designed to develop clinicians who teach and provide academic credit for scholarship of teaching and learning (SoTL). However, the potential benefits are more far-reaching than the individual. Key to this argument is the recognition that such programmes offer an environment where healthcare and educational scholarship meet, providing a fluid interface between theory, practice, and research . If qualThis expansion of provision in PGT-HPE, and the limited research to date, provides an opportunity to engage with the PGT-HPE/educational research nexus at an early stage in its evolution. We believe this opportunity requires we conceptualise these programmes as providing an opportunity for discussion and sharing between the clinic and the academe , and movAdopting an overarching theoretical framework (or “meta-framework”) that can be applied across multiple studies - even where different methodologies have been used within those studies - complements a common practice in many University departments, which is to take a thematic (or programmatic) approach to research activity in order to develop a coherent body of work, build critical mass, increase research outputs and reputation. One of the problems in designing a research programme is the balance between taking funding opportunities as they arise whilst maintaining sufficient focus to have an impact and develop expertise. Using a unifying theory helps to connect a range of different projects. In the next section, we presentThe delivery of PGT programmes is complex and multi-faceted. As a team with responsibility for delivering a large online programme in Clinical Education we found it challenging to consider the numerous and interconnected factors likely to influence the student experience. Online PGT programmes at the University of Edinburgh are delivered on a part-time basis, thus allowing students to continue their clinical work whilst studying. As experienced professionals, students are encouraged to share and discuss their experiences with each other, so enriching the learning environment for all. Online masters degrees typically run over three years and allow students to build relationships, both with faculty and each other during this period . StudentIn much of our research, we take an ecological view, locating the individual (and ourselves) within a wider environment. To this end, EST can be used as a theoretical meta-framework for understanding the interaction of different kinds of systems in which our PG students operate. EST was originally proposed in the context of child development and has since been used in a diverse range of health, educational, and other contexts  that operate at different distances from the child. These different systems represent the scope and immediacy of domains that influence the learning of the individual. For Bronfenbrenner, the microsystem was where the child was directly involved in social interactions and learning experiences . The mesosystem was comprised of connections between microsystems . Exosystems operated at a distance, influencing the individual but without their direct participation (e.g. government education departments). The macro-system was composed of societal features . The chronosystem was added later to account for the change in systems over time .Figure In the example given inThis model can be used with a range of social and educational theories to explore many aspects of PGT-HPE programmes and their wider relevance. It can be used to consider different contextual levels in which interactions occur and generate researchable questions, for example:••e.g. exploring the relationship between dissertation supervisor and supervisee (interactions at the level of a course (micro-system);••e.g. exploring the links between students experiences on PGT-HPE programmes and their impact in the workplace, and following this up over time ;locating individual students (and their learning) within interconnected systems (meso- and chrono-system);••e.g. exploring conceptualisations of evaluation of teaching and ideologies underpinning proposed outcomes of education (•the policy and practice context of faculty development (exo-system);•e.g. analysing the operationalisation and impact of faculty development policy and practice documents (in progress).critically reflecting on goals, design, scope, and potential impacts of PGT-HPE (macro-system);Using EST as a meta-framework, in combination with study-specific theories . Throughout their studies and, crucially, after graduation, our students engage with the wider community to a greater or lesser degree. Graduates take their learning back to their own areas of practice (meso-level), and can, in some cases, mobilise their new knowledge to impact on the macro and exo levels. Thus, alongside developing their own practice in clinical settings, there is a suggestion that those completing masters degrees are becoming the new leaders in the field , and canDrawing on our own experience, an illustrative example of such influence would be students from Poland learning about the system of appraisal in the UK as part of their studies. This learning is taken back to the individual’s hospital or university and considered in her or his own context, thus influencing the macro culture of medical education in Poland. Locating this activity within a network of ecological systems helps us to explore the impact of our postgraduate, online programme, and illustrates why the wider educational community, in clinical and university settings, should be interested in what is being taught and its practical consequences.PG students are at the centre of their own circle (micro-level), but also on the periphery of those of others’ (meso-level) see. Key to At the exo level, we are conscious that PGT-HPE (at any level) does not sit outside of its political and socio-economic context and boundaries between institutions of higher education, workplaces, and civic society are increasingly permeable . We explConsidering the chrono-level system has caused us to reflect on the temporal dimensions of education. Not only do we want to develop student agency across settings, but also in relation to adapting to, and integrating into, shifting contextual landscapes. We aspire to produce graduates who are able to negotiate changes in policy, technology, culture, economics and politics such that they not only maintain but also enhance their own agency and authority. Thus, considering the chrono-system helps us to think about the importance of adapting to dynamic, rather than static, contexts at each level , particularly in times of political and economic uncertainty. The current COVID-19 crisis further emphasises how the context of health professions education can change rapidly in a short space of time.In response to the issues noted above, as a programme team we have been working to develop a theoretically informed, coherent programme of research. To this end, we began by compiling a list of theories (or concepts) that we have found ourselves returning to in our scholarly discussions. This includes (but is not limited to) the work ofStarting at the micro level, we reflected that individual experiences would be constructed by direct experience of interactions with other students, technology, tutors, colleagues and family. Research at this level could be directed at exploring individuals’ backgrounds, motivations for PG-HPE and benefits gained. This takes account of our experience that students are a diverse group in terms of age, sex, professional background, career point, and culture. Reasons for engaging in study vary but initial work we have undertaken suggests such vocationally related programmes offer potential career advantages in terms of promotion and recognition. Knowledge gained from investigation at this level is valuable in its own right in terms of understanding our learners and the graduate attributes they acquire. However, the application of an overarching theoretical framework allows for moving beyond an individualistic approach. For example, our group has been exploring graduate attributes, looking at this in the context of the EST prompted us to think about this topic in terms of the wider organisational and social system using Bourdieu’s concepts of field, habitus, and capital  considering the mesosystem allows a focus on the influence of structure. We could, for example, explore postgraduate programmes in terms of the ways in which participants’ experiences and outcomes are shaped by the design of the curriculum. Knowledge gained at this level has potential value in terms of evaluating the curriculum in relation to its purpose. An important consideration is how such programmes are designed and delivered in practice; linking the programme as structure and the team as individuals. Our point is that one area cannot be viewed in isolationThe exo-system was considered by Bronfenbrenner to be out of reach of the individual, who was assumed not to have an impact on decision making at this level. An example of the exo-system impacting PGT students is the policy decisions by regulatory bodies, for example in the UK theThe literature on graduate attributes highlights the apparently transferable skills that graduates acquire on completion of their studies  resultinConsideration of the macro-system leads to exploration of the interaction between socio-cultural context and HPE. It provokes questions around how we as a society view and value education, and how this is embodied in policies, the design of programmes, and student engagement in those programmes. EST encourages us to think in broad theoretical terms about PGT-HPE and highlights the value of, for example, critical realism, evident in the work of one of our PhD candidates who has used this approach to explore why clinical educators feel they are not valued. Such approaches explicitly investigate the ecological system as it applies to PGT-HPE as a whole.In the context of innovation research,We have presented an example of how an overarching theoretical framework can help educators make sense of a range of teaching and research initiatives. We have offered ecological systems theory as an example of a potentially-valuable theoretical meta-framework that has enabled us to respond to the need for theoretically informed research into PGT-HPE that locates the individual student within a wider  context that involves interactions within and between different systems. We have found that EST can assist us in the process of integrating our critical reflection on our teaching and learning activities with developing a research programme. Using a framework to structure our thinking has enhanced our scholarly discussions about the characteristics, aims and impact of PGT-HPE. As others have found, there is no reason why some frameworks, such as EST, cannot be used for a wide range of purposes, including any kind of educational research to help scholars think about their particular topic and develop questions - whether that be PBL, widening access, professionalism, or teamwork to name but a few.This paper addresses an important topic in health professional education -- that is, the use and development of a meta-theoretical framework that assists in describing and positioning the findings of diverse studies and reflecting on practice.Derek Joneshttps://orcid.org/0000-0003-2197-7657Derek is the Programme Director of the PhD Clinical Education programme at the University of Edinburgh. ORCiD:Tim Fawnshttps://orcid.org/0000-0001-5014-2662Tim Fawns is the Deputy Programme Director of the MSc Clincial Education programme at the University of Edinburgh. ORCiD:Gillian Aitkenhttps://orcid.org/0000-0002-5492-1943Gill Aitken is the Programme Director of the MSc Clinical Education programme at the University of Edinburgh. ORCiD: This review has been migrated. The reviewer awarded 4 stars out of 5 A paper that emphasizes the importance of using a framework to structure research in postgraduate health professions education, that would reflect on practice. It is an informative and interesting article which provides a repository of valuable resources for research.Reviewer Expertise:NANo decision status is available This review has been migrated. The reviewer awarded 4 stars out of 5 I thank the authors for submitting this manuscript. I enjoyed reading and learning from their discussion on Bronfenbrenner's ecological systems theory as a theoretical framework for the teaching and research in postgraduate health professions education.I agree with the authors claiming that healthcare education is complex and multifaceted and that different perspectives are needed. Some (or most)of these come from the social sciences and represent an area that we, having a clinical background, are not so familiar with. In this sense, this paper is valuable and contributes to the discussion of using different/innovative perspectives and theoretical frameworks in health professions education.The first part of the manuscript, under the heading "Using EST to develop a research programme", presents a well-written introduction and justification. However, I was expecting this section to be more informative and explicit about EST.Figure 2 and the explanation of the authors to Bronfenbrenner's ecological systems theory applied to their student in their online course is informative and clearly illustrates the point on how this model can be applied to HPE research. As I read through, I found the section on "Using EST to develop a research programme" to be particularly relevant to allow the readers to transfer the authors' ideas to their own research settings.This paper provides a valuable resource for researchers as Bronfenbrenner's EST may be an applicable underpinning theory and provide structure to a vast range of studies conducted in HPE, whether it may be in an under or postgraduate context.Reviewer Expertise:NANo decision status is available This review has been migrated. The reviewer awarded 5 stars out of 5 really interesting article opens the mind in thinking differently regarding the thorough knowledge that starts from student till echo system and social structureReviewer Expertise:NANo decision status is available This review has been migrated. The reviewer awarded 4 stars out of 5 This paper highlights an exciting and innovative way of looking at Postgraduate education. Any education needs to be transformative. Particularly in the postgraduate HPE field ,it should have positive impact on the health care system , patients and the population. This model brings the individual learner and all other components together. I was able to use this model on a leadership program I was running and reflected on the various outcomes and found this way of thinking very useful when setting up new courses.Reviewer Expertise:NANo decision status is available This review has been migrated. The reviewer awarded 4 stars out of 5 This work is extraordinary in my point if view. It offers a reflection in the use of an already existing theory of the ecological system effect on learners to develop a program. This is extremely useful and replicable and has implications on program reform towards establishing a true educational impact on PG students.Reviewer Expertise:NANo decision status is available This review has been migrated. The reviewer awarded 5 stars out of 5 informative ,educative and informs the growing importance of medical education.Reviewer Expertise:NANo decision status is available


The simulation is one of the basic methods of medical education, which is often used for procedural skills training. However, the existing simulator lacks internal anatomical landmarks. The study developed a mixed-reality stimulator and evaluated its usability and feasibility in lumbar puncture training.The study recruited 40 subjects, including medical students, residents and faulty with varied levels of experience. Before training, participants completed the questionnaire about the basic information and watched a presentation about mixed reality. After practicing on mixed-reality stimulator, which provided internal anatomical structure, the examination was carried out and the results were documented. At the end of the training, trainees completed a survey of MR technology.In this study, participants generally believed that the MR technology was very realistic (90%), and that the presentation of internal anatomy could help the operation (95%). Moreover, 72.5% and 75%, respectively, strongly agreed that the MR technology promoted learning and should be used in medical training. After this training, the success rate of puncture and the puncture time were significantly improved in experienced and non-experienced participants.The existing simulator was easy to be transformed into MR simulator. This study showed the usability and feasibility of MR simulator in lumbar puncture training. As a potentially good tool to simulated medical skills training, next, MR technology would be developed and evaluated in more clinical skills teaching scenarios. Simulators are becoming increasingly important in medical education and its application in the field of anesthesiology and critical care medicine is currently being developed , 2. The However, traditional simulators often lack important internal landmarks and anatomical structures that can be identified by trainees. The information which displays is not intuitive and vivid enough to attract the attention of students and brings little gains to students in a specified time . VirtualMixed reality (MR) technology has the characteristics of combination of virtual and reality, real-time interaction and accurate matching, and MR can combine virtual images with entities and display the internal structure of objects , 11. As Lumbar puncture is an essential clinical skill for the clinician, especially for anesthesiologists . It is aIn this study, 3D anatomy image matching the mannequin was developed by using MR technology based on HoloLens glasses. The mannequin showing the internal anatomical structure was applied to the practice of lumbar puncture. The aim of this study is to evaluate the usability and feasibility of the application of MR technology in the training of lumbar puncture.This project was deemed exempt by Institutional Review Board of Shanghai Yueyang Integrated Traditional Chinese Medicine and Western Medicine Hospital affiliated to Shanghai University of Traditional Chinese Medicine.The lumbar vertebrae were scanned by CT with a thin layer of 0.625 mm, and the images were saved and converted into 3D images using Medical Rapid Prototyping technology of Medical Mixed reality surgery navigation System. The 3D image models were scaled on the stimulator in a ratio of 1:1, and the important internal landmarks in stimulator and anatomical structures of stimulator were seen by trainees wearing HoloLens glasses at the same time  techniques and their scores were recorded. And then, participants received the same basic anatomy training of LP, provided by XH and CG. After that, participants were guided to use the MR stimulator, which was demonstrated by CQ and HX, including adjusting and testing glasses to ensure comfort and accuracy of presentation. In the meantime, participants strengthened their understanding of spine anatomy through Glasses following the advice given by the trainer.The simulator used in the research was a common simulator without internal landmarks for lumbar puncture. Participant were asked to locate the L3-L4 interspace by palpation. The L3 and L4 spinous processes was correctly recognized, and the midpoint between the two spinous processes was used as the target of needle insertion. After the puncture space was accurately identified, the internal 3D image was projected on the simulator through the glasses, and the simulator with 3D image was presented on the computer screen at the same time. The trainees were allowed to understand the puncture position relative to the previously determined anatomical position. The trainees were asked to practice needle inserting with anatomy in view through glasses. Once participants were confident with their skill, they were asked to insert a needle on simulator without anatomy in view. If the needle inserted correctly into the subarachnoid space, the fluid flew out of the needle, simulating the outflow of cerebrospinal fluid. Otherwise, no liquid will flow out of the needle.Through the evaluation of the questionnaire and tests, two experienced evaluators independently recorded trainees’ achievements. The main items of the questionnaire included the correct identification of the anatomy, the correct angle and direction of the puncture needle, and the number of the puncture attempts. The operation time from the beginning of locating the puncture point to the end of needle fixation and the fluid flowing out of needle without anatomy in view by glasses were also recorded. At the end of training, participants completed a post-study questionnaire to conduct for the feedback survey after training. A 0-10point Likert scale was used to assess MR simulator subjectively. The scores of each attempt were compared to study the potential relationship before and after training.P value < 0.05 was considered statistically significant.This was a new tool in teaching study for testing of usability and feasibility, so there were no articles to refer to, and no power analysis size was required. SPSS, Windows® version 23.0 , was used for data analysis. Continuous variables were expressed as Mean ± SD, and categorical variables as counts . The difference comparison of continuous variables was completed by Student’s t-test, while chi-square test was used to analyze categorical variables. A two-sided The demographics of 40 participants with varied levels of experiences, including students, intern, faulty, resident, nurse anesthetist and fellow, are described in Table Table p < 0.05) (Table p < 0.05)  Table . Before 5) Table .Table 4CFor the teaching and research department of the teaching hospital, the mixed-reality simulator is easy to develop. Teaching centers with Glasses and simulators can be carried out under the guidance of patented technology. The results of this study demonstrated the usability and feasibility of the application of mixed-reality stimulator in lumbar puncture training. According to the feedback from different participants, mixed reality technology had great advantages in medical training, which can improve learning and skills. In addition, the skills of experienced and inexperienced participants had been improved after the application of the mixed reality technique, which proved that the mixed reality technique could provide useful training techniques for the various experienced participants.Compared to the AR technology, MR technology showed a significant improvement in knowledge retention in enhancing students' understanding of anatomy and physiology, in addition, it was reported higher levels of engagement and satisfaction with the technology than AR . MR alloThe application of MR in medicine is advancing rapidly. There is evidence to support its beneficial impact in many aspects of clinical teaching and medical training, such as medical teaching, preoperative discussion and programming, intraoperative navigation and remote consultation . For exaIn addition, the purpose of this study is to create an efficient training environment to teach and evaluate procedural skills at a relatively low cost, and a standard simulator was selected instead of a 3D print simulator owning to the high price of 3D models. Furthermore, 3D printing technology may be more suitable for personalized medicine than medical teaching because 3D model is not typical and representative in basic medical teaching . MoreoveEvery year, more than a million patients received lumbar puncture, with a failure rate of puncture about 30% in adults  and 40% This study was an attempt of MR in procedure skills. It was very important to find the potential limitations of this technology in medical education, which is helpful to improve teaching. The main complaints focused on HoloLens glasses in the study. For example, there was a slight time delay in the appearance of the glasses; the helmet was too heavy, causing soreness in the shoulder and neck; it was not very friendly to trainees who wear glasses. Despite these problems, they did not affect the trainees' ability to correctly identify the landmark structure and puncture. The research team is developing the real-time positioning and guidance function of the puncture needle in the procedure, which would further understand the relationship between the puncture needle and the surrounding tissues, as well as what may happen in the body. This improvement may increase the cost of teaching. However, as with any new technology, the cost of MR development and application will be reduced over time. The application of MR technology in medical education should be evaluated to ensure its efficacy and cost–benefit.This study demonstrates the usability and feasibility of mixed reality technology as a training tool for lumbar puncture. MR technology will provide a more immersive and effective training environment to learner to study more complex operations and will have a profound impact on the medical hands-on education. Thus, mixed reality is a promising and valuable approach that can be applied in medical simulation-education curricula in future.