[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-125956-en":3,"doc-seo-125956-105":31,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},125956,137451207643,"Noah","https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2",7,"Healthcare","TRIPOD+AI statement - updated guidance for reporting clinical prediction models that use regression or machine learning methods","TRIPOD+AI provides harmonised, transparent reporting guidance for studies that develop or evaluate clinical prediction models using regression or machine learning methods. The update replaces the 2015 TRIPOD statement and supersedes the 2015 checklist to address persistent concerns about incomplete and non-transparent reporting. The guidance includes a 27-item checklist, expanded recommendations for each item, and a dedicated TRIPOD+AI for Abstracts checklist to support appraisal, evaluation, and implementation by research users.","RESEARCH METHODS AND REPORTING  \nFor numbered affiliations see end of the article  \nCorrespondence to: G S Collins [gary.collins@csm.ox.ac. uk](gary.collins@csm.ox.ac. uk)[ ](gary.collins@csm.ox.ac. uk)(or @GSCollins on Twitter; ORCID 0000-0002-2772-2316) Additional material is published online only. To view please visit the journal online.  \nCite thisas: BMJ2024;385:e078378  \n[http://dx.doi.org/10.1136/](http://dx.doi.org/10.1136/)[ ](http://dx.doi.org/10.1136/)bmj-2023-078378  \nAccepted: 17 January 2024  \nTRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods  \nGary S Collins, 1 Karel G M Moons,2 Paula Dhiman, 1 Richard D Riley,3,4 Andrew L Beam, 5 Ben Van Calster,6,7 Marzyeh Ghassemi,8 Xiaoxuan Liu,9,10 Johannes B Reitsma,2 Maarten van Smeden,2 Anne-Laure Boulesteix, 11 Jennifer Catherine Camaradou, 12,13 Leo Anthony Celi, 14,15,16 Spiros Denaxas, 17,18 Alastair K Denniston,4,9 Ben Glocker, 19 Robert M Golub,20 Hugh Harvey,21 Georg Heinze,22 Michael M Hoffman,23,24,25,26  \nAndré Pascal Kengne,27 Emily Lam, 12 Naomi Lee,28 Elizabeth W Loder,29,30 Lena Maier-Hein,31 Bilal A Mateen, 17,32,33 Melissa D McCradden,34,35 Lauren Oakden-Rayner,36 Johan Ordish,37 Richard Parnell, 12 Sherri Rose,38 Karandeep Singh,39 Laure Wynants,40 Patricia Logullo 1  \nThe TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) statement was published in 2015 to provide the minimum reporting recommendations for studies developing or evaluating the performance of a prediction model. Methodological advances in the field of prediction have since included the widespread use of artificial intelligence (AI) powered by machine learning methods to develop prediction models. An update to the TRIPOD statement is thus needed. TRIPOD+AI provides harmonised guidance for reporting prediction model studies, irrespective  \nof whether regression modelling or machine learning methods have been used. The new checklist supersedes the TRIPOD 2015 checklist, which should no longer be used. This article describes the development of TRIPOD+AI and presents the expanded 27 item checklist with more detailed explanation of each reporting recommendation, and the TRIPOD+AI for Abstracts checklist. TRIPOD+AI aims to promote the complete, accurate, and transparent reporting of studies that develop a prediction model or evaluate its performance. Complete reporting will facilitate study appraisal, model evaluation, and model implementation.  \nSUMMARY POINTS  \nThere has been considerable interest and financial investment in developing prediction models by applying artificial intelligence (AI) methods, typically powered by advances in machine learning  \nTo ensure that a prediction model study is valuable to users, authors should prepare a transparent, complete, and accurate account of why the research was done, what they did, and what they found  \nAn update of the TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) statement aims to harmonise the landscape of prediction model studies using AI methods and to provide guidance regardless of whether regression models or machine learning methods have been used  \nThe TRIPOD+AI statement consists of a 27 item checklist, an expanded checklist that details reporting recommendations for each item, and a TRIPOD+AI for Abstracts checklist containing 13 items  \nTRIPOD+AI aims to assist authors in the complete reporting of their study and help peer reviewers, editors, policymakers, end users, and patients understand the data, methods, findings and conclusions of AI driven research  \nAdherence to the TRIPOD+AI reporting recommendations could encourage the improved use of research time, effort, and money  \nPrediction models are used across different healthcare settings. They are used to estimate an outcome value or risk. Most models estimate the probability of the presence of a p","cbCaipbfWGIWAZ6f","https://ap.wps.com/l/cbCaipbfWGIWAZ6f","pdf",291492,2,1,14,"English","en",105,"# TRIPOD+AI statement: updated reporting guidance\n## Purpose and background\n## Prediction model context and use\n## Summary points and structure of the guidance\n## Checklist and abstracts guidance","[{\"question\":\"What does TRIPOD+AI aim to improve in clinical prediction model reporting?\",\"answer\":\"TRIPOD+AI aims to promote complete, accurate, and transparent reporting so users can appraise studies, evaluate models, and support implementation.\"},{\"question\":\"Does TRIPOD+AI apply only to machine learning prediction models?\",\"answer\":\"No. TRIPOD+AI applies regardless of whether regression modelling or machine learning methods were used.\"},{\"question\":\"What resources are included in the TRIPOD+AI statement?\",\"answer\":\"It includes a 27-item checklist, an expanded checklist with detailed explanation for each item, and a TRIPOD+AI for Abstracts checklist with 13 items.\"}]","TRIPOD+AI statement - updated guidance for reporting clinical prediction models that use regression or machine learning methods | PDF",1785902226,35,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":29},"tripodai-statement-updated-guidance-for-reporting-clinical-prediction-models-that-use-regression-or-machine-learning-methods-125956","",{"@graph":37,"@context":86},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,48,51],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":20},"https://docshare.wps.com/document/","Document",{"item":49,"name":12,"@type":44,"position":50},"https://docshare.wps.com/document/healthcare/",3,{"item":52,"name":13,"@type":44,"position":53},"https://docshare.wps.com/document/tripodai-statement-updated-guidance-for-reporting-clinical-prediction-models-that-use-regression-or-machine-learning-methods-125956/125956/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":24,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":42,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-15","2026-08-05",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What does TRIPOD+AI aim to improve in clinical prediction model reporting?","Question",{"text":76,"@type":77},"TRIPOD+AI aims to promote complete, accurate, and transparent reporting so users can appraise studies, evaluate models, and support implementation.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"Does TRIPOD+AI apply only to machine learning prediction models?",{"text":81,"@type":77},"No. TRIPOD+AI applies regardless of whether regression modelling or machine learning methods were used.",{"name":83,"@type":74,"acceptedAnswer":84},"What resources are included in the TRIPOD+AI statement?",{"text":85,"@type":77},"It includes a 27-item checklist, an expanded checklist with detailed explanation for each item, and a TRIPOD+AI for Abstracts checklist with 13 items.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,119,124,129,132,136],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":20,"doc_module":4,"doc_module_name":47,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":47,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":47,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":117,"slug":118},40,"healthcare",{"id":120,"doc_module":4,"doc_module_name":47,"category_name":121,"show_sort_weight":122,"slug":123},8,"Research & Report",30,"research-report",{"id":125,"doc_module":4,"doc_module_name":47,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":47,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":47,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":47,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]