Evaluating artificial intelligence in medicine: phases of clinical research
Yoonyoung Park, Gretchen Purcell Jackson, Morgan A. Foreman, Daniel M. Gruen, Jianying Hu, Amar K. Das
Abstract
Increased scrutiny of artificial intelligence (AI) applications in healthcare highlights the need for real-world evaluations for effectiveness and unintended consequences. The complexity of healthcare, compounded by the user- and context-dependent nature of AI applications, calls for a multifaceted approach beyond traditional in silico evaluation of AI. We propose an interdisciplinary, phased research framework for evaluation of AI implementations in healthcare. We draw analogies to and highlight differences from the clinical trial phases for drugs and medical devices, and we present study design and methodological guidance for each stage.
Topics & Concepts
ScrutinyContext (archaeology)Health careImplementationUnintended consequencesComputer scienceArtificial intelligenceHealthcare systemManagement scienceData scienceEngineeringPolitical scienceProgramming languagePaleontologyLawBiologyArtificial Intelligence in Healthcare and EducationHealth Systems, Economic Evaluations, Quality of LifeMachine Learning in Healthcare