Clinical evaluation of artificial intelligence-enabled interventions.
Hogg, H D Jeffry Denniston, Alastair K Martindale, Alexander P L Liu, Xiaoxuan
Hogg, H D Jeffry
Denniston, Alastair K
Martindale, Alexander P L
Liu, Xiaoxuan
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.
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Date
2024-08-01
Type
Article
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Other
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Citation
Hogg HDJ, Martindale APL, Liu X, Denniston AK. Clinical Evaluation of Artificial Intelligence-Enabled Interventions. Invest Ophthalmol Vis Sci. 2024 Aug 1;65(10):10. doi: 10.1167/iovs.65.10.10.
Journal / Source Title
Investigative Ophthalmology and Visual Science
DOI
10.1167/iovs.65.10.10
PMID
39106058
Publisher
Association for Research in Vision and Ophthalmology
Publisher’s URL
https://www.ncbi.nlm.nih.gov/pmc/journals/1229/