Bioinformatics & Artificial Intelligence Laboratory, Center for Hypertension and Precision Medicine, Program in Physiological Genomics, Department of Physiology and Pharmacology, University of Toledo College of Medicine and Life Sciences, Toledo, Ohio, USA.
Compr Physiol. 2021 Sep 23;11(4):2455-2466. doi: 10.1002/cphy.c200034.
The advent of advances in machine learning (ML)-based techniques has popularized wide applications of artificial intelligence (AI) in various fields ranging from robotics to medicine. In recent years, there has been a surge in the application of AI to research in cardiovascular medicine, which is largely driven by the availability of large-scale clinical and multi-omics datasets. Such applications are providing a new perspective for a better understanding of cardiovascular disease (CVD), which could be used to develop novel diagnostic and therapeutic strategies. For example, studies have shown that ML has a substantial potential for early diagnosis of different types of CVD, prediction of adverse disease outcomes such as heart failure, and development of newer and personalized treatments. In this article, we provide an overview and discuss the current status of a wide range of AI applications, including machine learning, reinforcement learning, and deep learning, in cardiovascular medicine. © 2021 American Physiological Society. Compr Physiol 11:1-12, 2021.
机器学习（ML）技术的进步已经普及了人工智能（AI）在从机器人技术到医学等各个领域的广泛应用。近年来，人工智能在心血管医学研究中的应用呈激增态势，这在很大程度上是由于大规模临床和多组学数据集的出现。这些应用为更好地理解心血管疾病（CVD）提供了新的视角，可用于开发新的诊断和治疗策略。例如，研究表明，机器学习在不同类型 CVD 的早期诊断、心力衰竭等不良疾病结局的预测以及更新和个性化治疗的开发方面具有很大的潜力。在本文中，我们提供了一个概述，并讨论了机器学习、强化学习和深度学习等广泛的 AI 应用在心血管医学中的现状。 2021 年美国生理学会。综合生理学 11:1-12, 2021。
