Cardiovascular Applications of Artificial Intelligence in Research, Diagnosis, and Disease Management

V. Rajagopalan, Houwei Cao
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引用次数: 0

Abstract

Despite significant advancements in diagnosis and disease management, cardiovascular (CV) disorders remain the No. 1 killer both in the United States and across the world, and innovative and transformative technologies such as artificial intelligence (AI) are increasingly employed in CV medicine. In this chapter, the authors introduce different AI and machine learning (ML) tools including support vector machine (SVM), gradient boosting machine (GBM), and deep learning models (DL), and their applicability to advance CV diagnosis and disease classification, and risk prediction and patient management. The applications include, but are not limited to, electrocardiogram, imaging, genomics, and drug research in different CV pathologies such as myocardial infarction (heart attack), heart failure, congenital heart disease, arrhythmias, valvular abnormalities, etc.
人工智能在心血管研究、诊断和疾病管理中的应用
尽管在诊断和疾病管理方面取得了重大进展,但心血管(CV)疾病仍然是美国和世界各地的头号杀手,人工智能(AI)等创新和变革性技术越来越多地应用于心血管医学。在本章中,作者介绍了不同的人工智能和机器学习(ML)工具,包括支持向量机(SVM)、梯度增强机(GBM)和深度学习模型(DL),以及它们在推进CV诊断和疾病分类、风险预测和患者管理方面的适用性。应用包括但不限于心电图、成像、基因组学和不同心血管病理(如心肌梗死(心脏病发作)、心力衰竭、先天性心脏病、心律失常、瓣膜异常等)的药物研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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