Raising the Bar for Randomized Trials Involving Artificial Intelligence: The SPIRIT-Artificial Intelligence and CONSORT-Artificial Intelligence Guidelines.

Journal: The Journal of investigative dermatology
PMID: 33766511

Abstract

Artificial intelligence (AI)-based applications have the potential to improve the quality and efficiency of patient care in dermatology. Unique challenges in the development and validation of these technologies may limit their generalizability and real-world applicability. Before the widespread adoption of AI interventions, randomized trials should be conducted to evaluate their efficacy, safety, and cost effectiveness in clinical settings. The recent Standard Protocol Items: Recommendations for Interventional Trials-AI extension and Consolidated Standards of Reporting Trials-AI extension guidelines provide recommendations for reporting the methods and results of trials involving AI interventions. High-quality trials will provide gold standard evidence to support the adoption of AI for the benefit of patient care.

Authors

  • Matthew Taylor
    College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom; Health Data Research UK, London, United Kingdom.
  • Xiaoxuan Liu
    Birmingham Health Partners Centre for Regulatory Science and Innovation University of Birmingham Birmingham Reino Unido Birmingham Health Partners Centre for Regulatory Science and Innovation, University of Birmingham, Birmingham, Reino Unido.
  • Alastair Denniston
    Health Data Research UK, London, United Kingdom; Academic Unit of Ophthalmology, Institute of Inflammation and Ageing, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom; Department of Ophthalmology, University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom; Birmingham Health Partners Centre for Regulatory Science and Innovation, University of Birmingham, Birmingham, United Kingdom; NIHR Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, United Kingdom.
  • Andre Esteva
    Artera, Inc., Los Altos, CA.
  • Justin Ko
    Department of Dermatology, Stanford University, Stanford, California, USA.
  • Roxana Daneshjou
    1Department of Biomedical Data Science, Stanford School of Medicine, Stanford, California, USA; email: roxanad@stanford.edu.
  • An-Wen Chan
    Department of Medicine, Women's College Research Institute Women's College Hospital University of Toronto Ontario Canadá Department of Medicine, Women's College Research Institute, Women's College Hospital, University of Toronto, Ontario, Canadá.

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