Johnson KW et al. Artificial Intelligence in Cardiology. Journal of the American College of Cardiology 2018; 71(23): 2668-2679.

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Abstract

Artificial intelligence and machine learning are poised to influence nearly every aspect of the human condition, and cardiology is not an exception to this trend. This paper provides a guide for clinicians on relevant aspects of artificial intelligence and machine learning, reviews selected applications of these methods in cardiology to date, and identifies how cardiovascular medicine could incorporate artificial intelligence in the future. In particular, the paper first reviews predictive modeling concepts relevant to cardiology such as feature selection and frequent pitfalls such as improper dichotomization. Second, it discusses common algorithms used in supervised learning and reviews selected applications in cardiology and related disciplines. Third, it describes the advent of deep learning and related methods collectively called unsupervised learning, provides contextual examples both in general medicine and in cardiovascular medicine, and then explains how these methods could be applied to enable precision cardiology and improve patient outcomes.

The full list of the top 100 articles on artificial intelligence and artificial intelligence in medicine are published here:

Intelligence- Based Medicine
Artificial Intelligence and Human Cognition in Clinical Medicine and Healthcare.
Anthony Chang, MD, MBA, MPH, MS

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