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.

Journal: BMJ open
Published Date: Jul 9, 2021

Abstract

INTRODUCTION: The Transparent Reporting of a multivariable prediction model of Individual Prognosis Or Diagnosis (TRIPOD) statement and the Prediction model Risk Of Bias ASsessment Tool (PROBAST) were both published to improve the reporting and critical appraisal of prediction model studies for diagnosis and prognosis. This paper describes the processes and methods that will be used to develop an extension to the TRIPOD statement (TRIPOD-artificial intelligence, AI) and the PROBAST (PROBAST-AI) tool for prediction model studies that applied machine learning techniques.

Authors

  • Gary S Collins
    Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Botnar Research Centre, University of Oxford, Windmill Road, Oxford, OX3 7LD UK; Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
  • Paula Dhiman
    Center for Statistics in Medicine, University of Oxford, Oxford, UK.
  • Constanza L Andaur Navarro
    Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands c.l.andaurnavarro@umcutrecht.nl.
  • Jie Ma
    Respiratory Department, Beijing Hospital of Integrated Traditional Chinese and Western Medicine, Beijing, China.
  • Lotty Hooft
    Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
  • Johannes B Reitsma
    Julius Center for Health Sciences and Primary Care, Utrecht, Utrecht, Netherlands.
  • Patricia Logullo
    Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology & Musculoskeletal Sciences, University of Oxford, Oxford, UK.
  • Andrew L Beam
    Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
  • Lily Peng
    Google Inc, Mountain View, California.
  • Ben Van Calster
  • Maarten van Smeden
    Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
  • Richard D Riley
    School of Primary, Community and Social Care, Keele University, Keele, UK.
  • Karel Gm Moons
    Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.

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