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

M. Van Smeden; G. Heinze; B. Van Calster; F. W. Asselbergs; P. E. Vardas; N. Bruining; P. De Jaegere; J. H. Moore; S. Denaxas; A. L. Boulesteix; K. G. M. Moons

doi:10.1093/eurheartj/ehac238

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

M. Van Smeden^*
, G. Heinze
, B. Van Calster
, F. W. Asselbergs
, P. E. Vardas
, N. Bruining
, P. De Jaegere
, J. H. Moore
, S. Denaxas
, A. L. Boulesteix
, K. G. M. Moons

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

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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.

Original language	English
Pages (from-to)	2921-2930
Number of pages	10
Journal	European Heart Journal
Volume	43
Issue number	31
DOIs	https://doi.org/10.1093/eurheartj/ehac238
Publication status	Published - 14 Aug 2022

Bibliographical note

Publisher Copyright:
© 2022 The Author(s). Published by Oxford University Press on behalf of the European Society of Cardiology.

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title = "Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease",

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.",

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note = "Publisher Copyright: {\textcopyright} 2022 The Author(s). Published by Oxford University Press on behalf of the European Society of Cardiology.",

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month = aug,

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doi = "10.1093/eurheartj/ehac238",

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AU - Van Smeden, M.

AU - Heinze, G.

AU - Van Calster, B.

AU - Asselbergs, F. W.

AU - Vardas, P. E.

AU - Bruining, N.

AU - De Jaegere, P.

AU - Moore, J. H.

AU - Denaxas, S.

AU - Boulesteix, A. L.

AU - Moons, K. G. M.

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AB - 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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SP - 2921

EP - 2930

JO - European Heart Journal

JF - European Heart Journal

IS - 31

ER -

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

Abstract

Bibliographical note

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