Open science practices need substantial improvement in prognostic model studies in oncology using machine learning.

Journal: Journal of clinical epidemiology
Published Date: Oct 28, 2023

Abstract

OBJECTIVE: To describe the frequency of open science practices in a contemporary sample of studies developing prognostic models using machine learning methods in the field of oncology.

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.
  • Rebecca Whittle
    Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Centre for Statistics in Medicine, University of Oxford, Oxford, United Kingdom.
  • Garrett S Bullock
    Department of Orthopaedic Surgery, Wake Forest School of Medicine, Winston-Salem, NC, USA; Centre for Sport, Exercise and Osteoarthritis Research Versus Arthritis, University of Oxford, Oxford, United Kingdom.
  • Patricia Logullo
    Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology & Musculoskeletal Sciences, University of Oxford, Oxford, UK.
  • Paula Dhiman
    Center for Statistics in Medicine, University of Oxford, Oxford, UK.
  • Jennifer A de Beyer
    Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Centre for Statistics in Medicine, University of Oxford, Oxford, United Kingdom.
  • Richard D Riley
    School of Primary, Community and Social Care, Keele University, Keele, UK.
  • Michael M Schlussel
    Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Centre for Statistics in Medicine, University of Oxford, Oxford, United Kingdom.

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