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Development and validation pathways of artificial intelligence tools evaluated in randomised clinical trials.
George C M Siontis1, Romy Sweda2, Peter A Noseworthy3
1Department of Cardiology, Inselspital, University Hospital of Bern, Bern, Switzerland Georgios.Siontis@insel.ch.
BMJ Health & Care Informatics
|December 31, 2021
Summary
Development and validation pathways for artificial intelligence (AI) tools before AI-randomized controlled trials (AI-RCTs) show significant variation. Heterogeneous designs and reporting in AI-RCTs highlight the need for improved guidelines for AI clinical translation.
Area of Science:
- Medical Artificial Intelligence
- Clinical Trial Design
- Health Informatics
Background:
- Artificial intelligence (AI) tools are increasingly evaluated in clinical settings.
- Assessing the translational capability of AI tools presents complex challenges.
- Standardized pathways for AI tool development and validation are lacking.
Purpose of the Study:
- To map the development, training, validation, and external validation pathways of AI tools.
- To analyze AI tools evaluated in dedicated AI-randomized controlled trials (AI-RCTs).
- To identify patterns and variations in AI tool development and clinical evaluation.
Main Methods:
- Systematic search for peer-reviewed protocols and completed AI-RCTs.
- Identification of AI tool development and validation studies.
- Collection and evaluation of detailed information on AI tool development and validation processes.
Main Results:
- 23 AI-RCTs involving 18 unique AI tools (2009-2021) were identified.
- AI interventions favored in 82% of completed AI-RCTs (14/17).
- Significant variation observed in AI tool development, external validation, and clinical evaluation; published development studies available for only 10/18 tools.
Conclusions:
- Substantial heterogeneity exists in AI tool development and validation prior to AI-RCTs.
- AI-RCT protocols and reporting demonstrate considerable variation.
- Emerging guidelines aim to standardize AI development and clinical translation processes.
Keywords:
artificial intelligenceclinicaldata sciencedecision support systemsmachine learningmedical informaticsMore Related Videos
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