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  • Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence

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Medical publishing and peer review
Protocol
Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence

Authors

  • Gary S Collins Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology & Musculoskeletal Sciences, University of Oxford, Oxford, UKNIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, NIHR Oxford Biomedical Research Centre, Oxford, UK PubMed articlesGoogle scholar articles
  • Paula Dhiman Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology & Musculoskeletal Sciences, University of Oxford, Oxford, UKNIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, NIHR Oxford Biomedical Research Centre, Oxford, UK PubMed articlesGoogle scholar articles
  • Constanza L Andaur Navarro Julius Center for Health Sciences and Primary Care, Utrecht, Utrecht, Netherlands PubMed articlesGoogle scholar articles
  • Jie Ma Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology & Musculoskeletal Sciences, University of Oxford, Oxford, UK PubMed articlesGoogle scholar articles
  • Lotty Hooft Julius Center for Health Sciences and Primary Care, Utrecht, Utrecht, NetherlandsCochrane Netherlands, Julius Center for Health Sciences and Primary Care, Utrecht, Utrecht, Netherlands PubMed articlesGoogle scholar articles
  • Johannes B Reitsma Julius Center for Health Sciences and Primary Care, Utrecht, Utrecht, Netherlands PubMed articlesGoogle scholar articles
  • Patricia Logullo Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology & Musculoskeletal Sciences, University of Oxford, Oxford, UKNIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, NIHR Oxford Biomedical Research Centre, Oxford, UK PubMed articlesGoogle scholar articles
  • Andrew L Beam Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USADepartment of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA PubMed articlesGoogle scholar articles
  • Lily Peng Google Health, Google, Palo Alto, California, USA PubMed articlesGoogle scholar articles
  • Ben Van Calster Department of Development and Regeneration, KU Leuven, Leuven, BelgiumDepartment of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, NetherlandsEPI-Centre, KU Leuven, Leuven, Belgium PubMed articlesGoogle scholar articles
  • Maarten van Smeden Julius Center for Health Sciences and Primary Care, Utrecht, Utrecht, Netherlands PubMed articlesGoogle scholar articles
  • Richard D Riley Centre for Prognosis Research, School of Medicine, Keele University, Keele, UK PubMed articlesGoogle scholar articles
  • Karel GM Moons Julius Center for Health Sciences and Primary Care, Utrecht, Utrecht, NetherlandsCochrane Netherlands, Julius Center for Health Sciences and Primary Care, Utrecht, Utrecht, Netherlands PubMed articlesGoogle scholar articles
  1. Correspondence to Professor Gary S Collins; gary.collins{at}csm.ox.ac.uk
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Citation

Collins GS, Dhiman P, Andaur Navarro CL, et al
Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence
BMJ Open 2021;11:e048008. doi: 10.1136/bmjopen-2020-048008

Publication history

  • Received December 15, 2020
  • Accepted June 23, 2021
  • First published July 9, 2021.
Online issue publication 
July 09, 2021
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© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.