Artificial intelligence in cardiovascular imaging-principles, expectations, and limitations

被引：31

作者：

Antoniades, Charalambos ^{[1
,2
,3
,4
]}

Oikonomou, Evangelos K. ^{[1
,5
]}

机构：

[1] Univ Oxford, John Radcliffe Hosp, Div Cardiovasc Med, Radcliffe Dept Med, Headley Way, Oxford OX39DU, England

[2] British Heart Fdn Ctr Res Excellence, Oxford, England

[3] Oxford Univ Hosp NHS Fdn Trust, Natl Inst Hlth Res NIHR, John Radcliffe Hosp, Oxford Biomed Res Ctr, Headley Way, Oxford OX39DU, England

[4] Univ Oxford, John Radcliffe Hosp, Acute Vasc Imaging Ctr, Headley Way, Oxford OX39DU, England

[5] Yale New Haven Hosp, Yale Sch Med, Sect Cardiovasc Med, Dept Internal Med, New Haven, CT USA

来源：

EUROPEAN HEART JOURNAL | 2024年 / 45卷 / 15期

关键词：

MEDICINE; PREDICTION;

D O I：

10.1093/eurheartj/ehab678

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

Seven lessons for cardiologists in the era of artificial intelligence. When reviewing an artificial intelligence application, one needs to critically appraise the following domains: (1) Are artificial intelligence and machine learning necessary to address question of interest? (2) Are the input data of high quality? (3) Is an interpretation of the final algorithm attempted? (4) How is bias addressed? (5) Is appropriate external validation performed? (6) Are there any regulatory or ethical compliance concerns? (7) How much supervision does the final model require? © 2024 Oxford University Press. All rights reserved.

引用

页码：1322 / 1326

页数：5

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