TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods
Nuffield Orthopaedic Centre · University of Oxford · +37 more institutions
Abstract
The 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 of whether regression modelling or machine learning methods have been used. The new checklist supersedes the TRIPOD 2015…
Citation impact
- FWCI
- 203.93
- Percentile
- 100%
- References
- 99
Authors
34- GSGary S. CollinsCorresponding
Nuffield Orthopaedic Centre, University of Oxford
- KGKarel G.M. Moons
Utrecht University, University Medical Center Utrecht
- PDPaula Dhiman
Nuffield Orthopaedic Centre, University of Oxford
- RDRichard D Riley
NIHR Birmingham Biomedical Research Centre, University of Birmingham
- ALAndrew L. Beam
Harvard University
Topics & keywords
- Tripod (photography)
- Checklist
- Machine learning
- Computer science
- Artificial intelligence
- Engineering
- Psychology
Funding
- MIMassachusetts Institute of Technology
- NUNorthwestern University
- WTWellcome Trust
- NINational Institute for Health and Care Excellence
- URUK Research and Innovation
- CRCancer Research UK
- NINational Institute for Health and Care Research
- DODepartment of Health and Social Care
- UOUniversity of East Anglia
- UOUniversity of Warwick
- ICImperial College London
- UCUniversity College London
- UOUniversity of Oxford
- ECEuropean Commission
- UWUniversität Wien
- NONederlandse Organisatie voor Wetenschappelijk Onderzoek
- UOUniversity of Toronto
- UMUniversitair Medisch Centrum Utrecht
- KLKU Leuven
- MUMedizinische Universität Wien
- HFHospital for Sick Children
- UOUniversity of Cape Town
- VRVlaamse regering
- FSFeinberg School of Medicine
- MRMedical Research CouncilAwards: HDR-23004, HDR-23002, MR/V038168/1
- EAEngineering and Physical Sciences Research CouncilAward: EP/Y018516/1
- NHNational Heart, Lung, and Blood Institute
- NINational Institute of Diabetes and Digestive and Kidney Diseases
- HDHealth Data Research UK