| 机器学习在心血管疾病辅助诊断中的研究:现状与未来进展 |
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| 引用本文： | 王 丽1 计礼丽2 陆浩轩1 谢燕青1 何文明1. 机器学习在心血管疾病辅助诊断中的研究:现状与未来进展[J]. 宁波大学学报(理工版), 2023, 0(3): 102-107 |
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| 作者姓名： | 王 丽1 计礼丽2 陆浩轩1 谢燕青1 何文明1 |
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| 作者单位： | 1.宁波大学附属第一医院, 浙江 宁波 315020; 2.宁波大学 医学部, 浙江 宁波 315211 |
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| 基金项目： | 浙江省卫生科技计划（WKJ-ZJ-2137）；;宁波市自然科学基金（2021J240）； |
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| 摘 要： | 心血管疾病具有高发病率、高住院率、高致残率、高死亡率等特征,伴随高额的治疗疾病负担,早期准确诊断心血管疾病意义重大.以机器学习(ML)为代表的人工智能心血管疾病辅助诊断技术为诊断心血管疾病提供了新方法.基于ML疾病诊断技术日趋成熟,且在各类心血管疾病中取得诸多进展,包括冠心病、心力衰竭及心律失常等.本文综述了ML在心血管疾病辅助诊断中的技术背景和研究现状,分析了该领域在临床转化应用方面的挑战,并对未来研究进行了展望.
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| 关 键 词： | 心血管疾病 机器学习 人工智能 辅助诊断 |
Research in machine learning for auxiliary diagnosis of cardiovascular diseases: Current status and future prospects |
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| WANG Li1,JI Lili2,LU Haoxuan1,XIE Yanqing1,HE Wenming1. Research in machine learning for auxiliary diagnosis of cardiovascular diseases: Current status and future prospects[J]. Journal of Ningbo University(Natural Science and Engineering Edition), 2023, 0(3): 102-107 |
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| Authors: | WANG Li1 JI Lili2 LU Haoxuan1 XIE Yanqing1 HE Wenming1 |
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| Affiliation: | 1.The First Affiliated Hospital of Ningbo University, Ningbo 315020, China;2.Health Science Center, Ningbo University, Ningbo 315211, China |
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| Abstract: | Cardiovascular diseases are characterized by high morbidity, hospitalization, disability, and mortality rates, accompanied with a high disease burden. Therefore, early and accurate diagnosis of cardiovascular diseases is of great significance. The artificial intelligence cardiovascular disease aided diagnosis technology represented by machine learning (ML) provides a new approach to solve the above problems. ML-based disease diagnosis techniques are becoming increasingly mature and have advantages in various cardiovascular diseases, including heart failure, coronary atherosclerotic heart disease, and arrhythmias. This paper reviews the technical background and current research development of ML in the ancillary diagnosis of cardiovascular diseases. It also analyzes the challenges and prospects for translational clinical applications in this field. |
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| Keywords: | cardiovascular diseases machine learning artificial intelligence auxiliary diagnosis |
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