Advances in the application of machine learning based on intravascular ultrasound in coronary artery disease
Xiong Xin, Deng Yongzhi
Department of Cardiovascular Surgery, the Affiliated Cardiovascular Hospital of Shanxi Medical University, Shanxi Cardiovascular Hospital (Institute), Shanxi Clinical Medical Research Center of Cardiovascular Disease, Taiyuan 030024, China
Abstract：Intravascular ultrasound(IVUS) is an essential source of information for the clinical diagnosis and management of coronary artery disease. The diagnosis and management of coronary artery disease heavily relies on the medical professionals′ interpretation of IVUS images. Machine learning can analyze data, create medical diagnostic models, and extract information from IVUS images that human eyes cannot perceive. These capabilities help enhance the diagnosis of coronary artery disease, forecast patients′ disease states and clinical outcomes, and play a significant role in supporting clinical work. This article discusses the limitations and potential applications of machine learning techniques in IVUS for coronary artery imaging.
熊鑫 邓勇志. 基于血管内超声的机器学习在冠状动脉病变中的
研究进展[J]. 中华诊断学电子杂志, 2023, 11(3): 153-157.
Xiong Xin, Deng Yongzhi. Advances in the application of machine learning based on intravascular ultrasound in coronary artery disease. zhzdx, 2023, 11(3): 153-157.
