Shu Songren, Ren Jie, Song Jiangping
State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College.
Circ J. 2021 Aug 25;85(9):1416-1425. doi: 10.1253/circj.CJ-20-1121. Epub 2021 Apr 22.
With the rapid development of artificial intelligence (AI) and machine learning (ML), as well as the arrival of the big data era, technological innovations have occurred in the field of cardiovascular medicine. First, the diagnosis of cardiovascular diseases (CVDs) is highly dependent on assistive examinations, the interpretation of which is time consuming and often limited by the knowledge level and clinical experience of doctors; however, AI could be used to automatically interpret the images obtained in auxiliary examinations. Second, some of the predictions of the incidence and prognosis of CVDs are limited in clinical practice by the use of traditional prediction models, but there may be occasions when AI-based prediction models perform well by using ML algorithms. Third, AI has been used to assist precise classification of CVDs by integrating a variety of medical data from patients, which helps better characterize the subgroups of heterogeneous diseases. To help clinicians better understand the applications of AI in CVDs, this review summarizes studies relating to AI-based diagnosis, prediction, and classification of CVDs. Finally, we discuss the challenges of applying AI to cardiovascular medicine.
随着人工智能（AI）和机器学习（ML）的迅速发展，以及大数据时代的到来，心血管医学领域发生了技术创新。首先，心血管疾病（CVD）的诊断高度依赖辅助检查，而对这些检查结果的解读既耗时，又常常受医生知识水平和临床经验的限制；然而，AI可用于自动解读辅助检查中获取的图像。其次，CVD发病率和预后的一些预测在临床实践中受传统预测模型的限制，但基于AI的预测模型利用ML算法可能会有出色表现。第三，AI已被用于通过整合患者的各种医学数据来辅助CVD的精准分类，这有助于更好地描述异质性疾病的亚组特征。为帮助临床医生更好地理解AI在CVD中的应用，本综述总结了与基于AI的CVD诊断、预测和分类相关的研究。最后，我们讨论了将AI应用于心血管医学所面临的挑战。
