Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease
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- Maarten van Smeden
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University , Universiteitsweg 100, 3584 CG Utrecht , The Netherlands
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- Georg Heinze
- Section for Clinical Biometrics, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna , Vienna , Austria
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- Ben Van Calster
- Department of Development and Regeneration , KU Leuven, Leuven , Belgium
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- Folkert W Asselbergs
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University , Utrecht , The Netherlands
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- Panos E Vardas
- Department of Cardiology, Heraklion University Hospital , Heraklion , Greece
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- Nico Bruining
- Department of Cardiology , Erasmus MC , Thorax Center, Rotterdam , The Netherlands
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- Peter de Jaegere
- Department of Cardiology , Erasmus MC, Thorax Center, Rotterdam , The Netherlands
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- Jason H Moore
- Department of Computational Biomedicine, Cedars-Sinai Medical Center , Los Angeles, CA , USA
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- Spiros Denaxas
- Health Data Research UK and Institute of Health Informatics, University College London , London , UK
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- Anne Laure Boulesteix
- Institute for Medical Information Processing, Biometry and Epidemiology , LMU Munich , Germany
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- Karel G M Moons
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University , Universiteitsweg 100, 3584 CG Utrecht , The Netherlands
Abstract
<jats:title>Abstract</jats:title><jats:p>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.</jats:p>
Journal
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- European Heart Journal
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European Heart Journal 43 (31), 2921-2930, 2022-05-26
Oxford University Press (OUP)
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Details 詳細情報について
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- CRID
- 1360580236997932288
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- ISSN
- 15229645
- 0195668X
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- Data Source
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- Crossref