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人工智能在多模态心血管成像中的应用:最新综述。

Applications of artificial intelligence in multimodality cardiovascular imaging: A state-of-the-art review.

机构信息

Section of Cardiovascular Imaging, Robert and Suzanne Tomsich Department of Cardiovascular Medicine, Sydell and Arnold Miller Family Heart, Vascular and Thoracic Institute, Cleveland Clinic, OH, USA.

Section of Cardiovascular Imaging, Robert and Suzanne Tomsich Department of Cardiovascular Medicine, Sydell and Arnold Miller Family Heart, Vascular and Thoracic Institute, Cleveland Clinic, OH, USA.

出版信息

Prog Cardiovasc Dis. 2020 May-Jun;63(3):367-376. doi: 10.1016/j.pcad.2020.03.003. Epub 2020 Mar 19.

Abstract

There has been a tidal wave of recent interest in artificial intelligence (AI), machine learning and deep learning approaches in cardiovascular (CV) medicine. In the era of modern medicine, AI and electronic health records hold the promise to improve the understanding of disease conditions and bring a personalized approach to CV care. The field of CV imaging (CVI), incorporating echocardiography, cardiac computed tomography, cardiac magnetic resonance imaging and nuclear imaging, with sophisticated imaging techniques and high volumes of imaging data, is primed to be at the forefront of the revolution in precision cardiology. This review provides a contemporary overview of the CVI imaging applications of AI, including a critique of the strengths and potential limitations of deep learning approaches.

摘要

近年来,人工智能(AI)、机器学习和深度学习方法在心血管(CV)医学领域受到了极大的关注。在现代医学时代,人工智能和电子健康记录有望改善对疾病状况的理解,并为 CV 护理带来个性化方法。心血管成像(CVI)领域,结合了超声心动图、心脏计算机断层扫描、心脏磁共振成像和核医学成像,以及复杂的成像技术和大量的成像数据,正处于精准心脏病学革命的前沿。本文综述了 AI 在 CVI 成像中的应用,包括对深度学习方法的优势和潜在局限性的评价。

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