Successes and challenges of artificial intelligence in cardiology

Frontiers in Digital Health

Digital Health

Derek S. Chew¹  Derek V. Exner¹  Bert Vandenberk²  Sunny Gupta³  Dinesh Prasana⁴ 

[1] Department of Cardiac Sciences, Libin Cardiovascular Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada;Department of Cardiac Sciences, Libin Cardiovascular Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada;Department of Cardiovascular Sciences, KU Leuven, Leuven, Belgium;Intelense Inc., Markham, ON, Canada;Intelense Inc., Markham, ON, Canada;IOT/AI- Caliber Interconnect Pvt Ltd., Coimbatore, India;

关键词: artificial intelligence;    big data;    synthetic data;    cardiology;    electrophysiolgy;   

DOI  :  10.3389/fdgth.2023.1201392

 received in 2023-04-11, accepted in 2023-06-19,  发布年份 2023

来源: Frontiers

【 摘 要 】

In the past decades there has been a substantial evolution in data management and data processing techniques. New data architectures made analysis of big data feasible, healthcare is orienting towards personalized medicine with digital health initiatives, and artificial intelligence (AI) is becoming of increasing importance. Despite being a trendy research topic, only very few applications reach the stage where they are implemented in clinical practice. This review provides an overview of current methodologies and identifies clinical and organizational challenges for AI in healthcare.

【 授权许可】

Unknown   
© 2023 Vandenberk, Chew, Prasana, Gupta and Exner.