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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 G M.
Afiliação
  • van Smeden M; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG Utrecht, The Netherlands.
  • Heinze G; Section for Clinical Biometrics, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria.
  • Van Calster B; Department of Development and Regeneration, KU Leuven, Leuven, Belgium.
  • Asselbergs FW; EPI Centre, KU Leuven, Leuven, Belgium.
  • Vardas PE; Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, The Netherlands.
  • Bruining N; Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
  • de Jaegere P; Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK.
  • Moore JH; Health Data Research UK and Institute of Health Informatics, University College London, London, UK.
  • Denaxas S; Department of Cardiology, Heraklion University Hospital, Heraklion, Greece.
  • Boulesteix AL; Heart Sector, Hygeia Hospitals Group, Athens, Greece.
  • Moons KGM; Department of Cardiology, Erasmus MC , Thorax Center, Rotterdam, The Netherlands.
Eur Heart J ; 43(31): 2921-2930, 2022 08 14.
Article em En | MEDLINE | ID: mdl-35639667
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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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Doenças Cardiovasculares Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Doenças Cardiovasculares Idioma: En Ano de publicação: 2022 Tipo de documento: Article