Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease

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 GM

doi:10.1093/eurheartj/ehac238

Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease

Author:

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 GM

Keywords:

Science & Technology, Life Sciences & Biomedicine, Cardiac & Cardiovascular Systems, Cardiovascular System & Cardiology, Digital health, Artificial intelligence, Machine learning, Diagnosis, Prognosis, Prediction, INDIVIDUAL PROGNOSIS, DIAGNOSIS TRIPOD, RISK, PERFORMANCE, VALIDATION, HEALTH, IMPACT, CARE, Artificial Intelligence, Cardiovascular Diseases, Health Personnel, Humans, Software, C24M/20/064#55737126, 1102 Cardiorespiratory Medicine and Haematology, 1103 Clinical Sciences, Cardiovascular System & Hematology, 3201 Cardiovascular medicine and haematology, 3202 Clinical sciences

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.