心脏病学中的人工智能

Q4 Medicine
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引用次数: 0

摘要

在人工智能(AI)的第一波浪潮中,基于规则的专家系统被开发出来,并取得了一定的成功,以帮助那些在特定领域缺乏专业知识的通才。人工智能的第二波浪潮,最初被称为人工神经网络,但现在被称为机器学习,在20世纪80年代开始对多层网络产生影响。深度学习能够实现自动特征发现,在包括心脏病学在内的多个医学学科中取得了惊人的成功,从自动图像分析到窦性心律期间房颤的心电图特征识别。机器学习现在已经被纳入英国国家医疗服务体系(NHS)的长期计划,但它的广泛采用可能会受到深度神经网络“黑箱”性质的限制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial intelligence in cardiology
In the first wave of artificial intelligence (AI), rule-based expert systems were developed, with modest success, to help generalists who lacked expertise in a specific domain. The second wave of AI, originally called artificial neural networks but now described as machine learning, began to have an impact with multilayer networks in the 1980s. Deep learning, which enables automated feature discovery, has enjoyed spectacular success in several medical disciplines, including cardiology, from automated image analysis to the identification of the electrocardiographic signature of atrial fibrillation during sinus rhythm. Machine learning is now embedded within the NHS Long-Term Plan in England, but its widespread adoption may be limited by the “black-box” nature of deep neural networks.
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来源期刊
Heart and Metabolism
Heart and Metabolism Medicine-Endocrinology, Diabetes and Metabolism
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