Artificial intelligence in cardiology

被引：16

作者：

Bonderman, Diana ^{[1
]}

机构：

[1] Med Univ Vienna, Dept Cardiol, Wahringer Gurtel 18-20, A-1090 Vienna, Austria

来源：

WIENER KLINISCHE WOCHENSCHRIFT | 2017年 / 129卷 / 23-24期

关键词：

Decision-making; Cardiology; Artificial intelligence; PRESERVED EJECTION FRACTION; HEART-FAILURE; PHENOTYPE;

D O I：

10.1007/s00508-017-1275-y

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

Decision-making is complex in modern medicine and should ideally be based on available data, structured knowledge and proper interpretation in the context of an individual patient. Automated algorithms, also termed artificial intelligence that are able to extract meaningful patterns from data collections and build decisions upon identified patterns may be useful assistants in clinical decision-making processes. In this article, artificial intelligence-based studies in clinical cardiology are reviewed. The text also touches on the ethical issues and speculates on the future roles of automated algorithms versus clinicians in cardiology and medicine in general.

引用

页码：866 / 868

页数：3

共 8 条

[1] Functional Status, Pulmonary Artery Pressure, and Clinical Outcomes in Heart Failure With Preserved Ejection Fraction [J].

Dalos, Daniel ;

Mascherbauer, Julia ;

Zotter-Tufaro, Caroline ;

Duca, Franz ;

Kammerlander, Andreas A. ;

Aschauer, Stefan ;

Bonderman, Diana .

JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, 2016, 68 (02) :189-199

[2] Machine Learning of Three-dimensional Right Ventricular Motion Enables Outcome Prediction in Pulmonary Hypertension: A Cardiac MR Imaging Study [J].

Dawes, Timothy J. W. ;

de Marvao, Antonio ;

Shi, Wenzhe ;

Fletcher, Tristan ;

Watson, Geoffrey M. J. ;

Wharton, John ;

Rhodes, Christopher J. ;

Howard, Luke S. G. E. ;

Gibbs, J. Simon R. ;

Rueckert, Daniel ;

Cook, Stuart A. ;

Wilkins, Martin R. ;

O'Regan, Declan P. .

RADIOLOGY, 2017, 283 (02) :381-390

[3]

Kahnerman D, 2016, HARV BUS REV, VR10, P36

[4] The HFpEF Obesity Phenotype The Elephant in the Room [J].

Kitzman, Dalane W. ;

Shah, Sanjiv J. .

JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, 2016, 68 (02) :200-203

[5] Connecting the Dots From Big Data to Healthy Heart [J].

Lau, Edward ;

Watson, Karol E. ;

Ping, Peipei .

CIRCULATION, 2016, 134 (05) :362-364

[6] Evidence Supporting the Existence of a Distinct Obese Phenotype of Heart Failure With Preserved Ejection Fraction [J].

Obokata, Masaru ;

Reddy, Yogesh N. V. ;

Pislaru, Sorin V. ;

Melenovsky, Vojtech ;

Borlaug, Barry A. .

CIRCULATION, 2017, 136 (01) :6-+

[7] Differences in Repolarization Heterogeneity Among Heart Failure With Preserved Ejection Fraction Phenotypic Subgroups [J].

Oskouie, Suzanne K. ;

Prenner, Stuart B. ;

Shah, Sanjiv J. ;

Sauer, Andrew J. .

AMERICAN JOURNAL OF CARDIOLOGY, 2017, 120 (04) :601-606

[8] Phenomapping for Novel Classification of Heart Failure With Preserved Ejection Fraction [J].

Shah, Sanjiv J. ;

Katz, Daniel H. ;

Selvaraj, Senthil ;

Burke, Michael A. ;

Yancy, Clyde W. ;

Gheorghiade, Mihai ;

Bonow, Robert O. ;

Huang, Chiang-Ching ;

Deo, Rahul C. .

CIRCULATION, 2015, 131 (03) :269-+

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