Muhammad Umer Riaz Gondal, Hassan Atta Mehdi, Raja Ram Khenhrani, Neha Kumari, Muhammad Faizan Ali, Sooraj Kumar, Maria Faraz, Jahanzeb Malik
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引用次数: 0
Abstract
Machine learning (ML), a subset of artificial intelligence (AI) centered on machines learning from extensive datasets, stands at the forefront of a technological revolution shaping various facets of society. Cardiovascular medicine has emerged as a key domain for ML applications, with considerable efforts to integrate these innovations into routine clinical practice. Within cardiac electrophysiology, ML applications, especially in the automated interpretation of electrocardiograms, have garnered substantial attention in existing literature. However, less recognized are the diverse applications of ML in cardiac electrophysiology and arrhythmias, spanning basic science research on arrhythmia mechanisms, both experimental and computational, as well as contributions to enhanced techniques for mapping cardiac electrical function and translational research related to arrhythmia management. This comprehensive review delves into various ML applications within the scope of this journal, organized into 3 parts. The first section provides a fundamental understanding of general ML principles and methodologies, serving as a foundational resource for readers interested in exploring ML applications in arrhythmia research. The second part offers an in-depth review of studies in arrhythmia and electrophysiology that leverage ML methodologies, showcasing the broad potential of ML approaches. Each subject is thoroughly outlined, accompanied by a review of notable ML research advancements. Finally, the review delves into the primary challenges and future perspectives surrounding ML-driven cardiac electrophysiology and arrhythmias research.
机器学习(ML)是人工智能(AI)的一个子集,其核心是机器从大量数据集中进行学习。心血管医学已成为人工智能应用的关键领域,人们正努力将这些创新融入常规临床实践中。在心脏电生理学领域,ML 应用,尤其是在心电图自动解读方面的应用,已在现有文献中引起了广泛关注。然而,人们对 ML 在心脏电生理学和心律失常方面的各种应用认识较少,这些应用涵盖了心律失常机制的基础科学研究(包括实验研究和计算研究),以及对心电功能绘图增强技术和心律失常管理相关转化研究的贡献。这篇综合评论深入探讨了本期刊范围内的各种 ML 应用,分为三个部分。第一部分提供了对一般 ML 原理和方法的基本了解,为有兴趣探索 ML 在心律失常研究中应用的读者提供了基础资源。第二部分深入评述了利用 ML 方法进行的心律失常和电生理学研究,展示了 ML 方法的广泛潜力。每一个主题都有详尽的概述,并对著名的 ML 研究进展进行了回顾。最后,综述深入探讨了 ML 驱动的心脏电生理学和心律失常研究面临的主要挑战和未来展望。
期刊介绍:
The mission of Cardiology in Review is to publish reviews on topics of current interest in cardiology that will foster increased understanding of the pathogenesis, diagnosis, clinical course, prevention, and treatment of cardiovascular disorders. Articles of the highest quality are written by authorities in the field and published promptly in a readable format with visual appeal