Key result
A framework of 12 critical questions was proposed to assist cardiovascular health professionals in critically appraising the development, validation, and clinical utility of AI prediction models.
Provides a practical framework of 12 critical questions for clinicians to critically appraise AI-based prediction models in cardiovascular medicine.
Equips clinicians to critically appraise AI CV prediction models before adoption; extends evaluation standards for researchers on validity and utility.
The medical field has seen a rapid increase in the development of artificial intelligence (AI)-based prediction models. With the introduction of such AI-based prediction model tools and software in cardiovascular patient care, the cardiovascular researcher and healthcare professional are challenged to understand the opportunities as well as the limitations of the AI-based predictions. In this article, we present 12 critical questions for cardiovascular health professionals to ask when confronted with an AI-based prediction model. We aim to support medical professionals to distinguish the AI-based prediction models that can add value to patient care from the AI that does not.
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Smeden et al. (2022) conducted a review in Cardiovascular disease. Artificial intelligence-based prediction models was evaluated. A framework of 12 critical questions was proposed to assist cardiovascular health professionals in critically appraising the development, validation, and clinical utility of AI prediction models.
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