Clinical Evaluation of Artificial Intelligence-Enabled Interventions.

Journal: Investigative ophthalmology & visual science
PMID: 39106058

Abstract

Artificial intelligence (AI) health technologies are increasingly available for use in real-world care. This emerging opportunity is accompanied by a need for decision makers and practitioners across healthcare systems to evaluate the safety and effectiveness of these interventions against the needs of their own setting. To meet this need, high-quality evidence regarding AI-enabled interventions must be made available, and decision makers in varying roles and settings must be empowered to evaluate that evidence within the context in which they work. This article summarizes good practices across four stages of evidence generation for AI health technologies: study design, study conduct, study reporting, and study appraisal.

Authors

  • H D Jeffry Hogg
    University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom.
  • Alexander P L Martindale
    Brighton and Sussex Medical School, Brighton, UK.
  • 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 K Denniston
    Centre for Patient Reported Outcomes Research Institute of Applied Health Research University of Birmingham Birmingham Reino Unido Centre for Patient Reported Outcomes Research, Institute of Applied Health Research, University of Birmingham, Birmingham, Reino Unido.

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