Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease . (26th May 2022)

• Record Type: Journal Article
• Authors: van Smeden, Maarten; Heinze, Georg; Van Calster, Ben; Asselbergs, Folkert W; Vardas, Panos E; Bruining, Nico; de Jaegere, Peter; Moore, Jason H; Denaxas, Spiros; Boulesteix, Anne Laure; Moons, Karel G M
• Is Part Of: European heart journal. Volume 43:Number 31(2022)
• Page Start: 2921
• Page End: 2930
• Publication Date: 2022-05-26
• Subjects: Digital health -- Artificial intelligence -- Machine learning -- Diagnosis -- Prognosis -- Prediction; Cardiology -- Periodicals; Heart -- Diseases -- Periodicals; 616.12005
• DOI: 10.1093/eurheartj/ehac238
• Languages: English
• ISSNs: 0195-668X

Abstract

Abstract: 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. Graphical Abstract: Graphical Abstract Twelve critical questions to be asked by readers and reviewers when confronted with prediction models that are based on AI. Audio Abstract: