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

被引：68

作者：

van Smeden, Maarten ^{[1
]}

Heinze, Georg ^{[2
]}

Van Calster, Ben ^{[3
,4
,5
]}

Asselbergs, Folkert W. ^{[6
,7
,8
,9
]}

Vardas, Panos E. ^{[10
,11
]}

Bruining, Nico ^{[12
]}

de Jaegere, Peter ^{[12
]}

Moore, Jason H. ^{[13
]}

Denaxas, Spiros ^{[8
,9
,14
]}

Boulesteix, Anne-Laure ^{[15
]}

Moons, Karel G. M. ^{[1
]}

机构：

[1] Univ Utrecht, Univ Med Ctr Utrecht, Julius Ctr Hlth Sci & Primary Care, Univ Weg 100, NL-3584 CG Utrecht, Netherlands

[2] Med Univ Vienna, Sect Clin Biometr, Ctr Med Stat Informat & Intelligent Syst, Vienna, Austria

[3] Katholieke Univ Leuven, Dept Dev & Regenerat, Leuven, Belgium

[4] Katholieke Univ Leuven, EPI Ctr, Leuven, Belgium

[5] Leiden Univ, Dept Biomed Data Sci, Med Ctr, Leiden, Netherlands

[6] Univ Utrecht, Univ Med Ctr Utrecht, Div Heart & Lungs, Dept Cardiol, Utrecht, Netherlands

[7] UCL, Inst Cardiovasc Sci, Fac Populat Hlth Sci, London, England

[8] UCL, Hlth Data Res UK, London, England

[9] UCL, Inst Hlth Informat, London, England

[10] Herakl Univ Hosp, Dept Cardiol, Iraklion, Greece

[11] Hygeia Hosp Grp, Heart Sect, Athens, Greece

[12] Erasmus MC, Thorax Ctr, Dept Cardiol, Rotterdam, Netherlands

[13] Cedars Sinai Med Ctr, Dept Computat Biomed, Los Angeles, CA 90048 USA

[14] Alan Turing Inst, London, England

[15] Ludwig Maximilians Univ Munchen, Inst Med Informat Proc Biometry & Epidemiol, Munich, Germany

来源：

EUROPEAN HEART JOURNAL | 2022年 / 43卷 / 31期

基金：

美国国家卫生研究院;

关键词：

Digital health; Artificial intelligence; Machine learning; Diagnosis; Prognosis; Prediction; RISK; PERFORMANCE; VALIDATION; DIAGNOSIS; HEALTH; IMPACT; CARE;

D O I：

10.1093/eurheartj/ehac238

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

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.

引用

页码：2921 / 2930

页数：10

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