机器学习在不良心血管事件诊断中的应用综述  

Review of Application of Machine Learning in the Diagnosis of Adverse Cardiovascular Events

作　　者：柯盼盼 陈胜[1] 李珂然 KE Pan-pan;CHEN Sheng;LI Ke-ran(School of Optical-Electrical and Computer Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)

机构地区：[1]上海理工大学光电信息与计算机工程学院,上海200093

出　　处：《软件导刊》2023年第2期212-217,共6页Software Guide

基　　金：国家自然科学基金项目(81101116)。

摘　　要：急性冠状动脉综合征是由冠状动脉血流减少引起的一种急性严重综合征,是造成全球范围内患者死亡和长期严重残疾的重要原因,因此预测不良心血管事件对患者的风险排查、早期诊断和治疗等有着重要价值。机器学习可以探索新的可能性,揭示患者信息统计大数据中的隐藏关系,将对心血管疾病的辅助诊断和预后分析产生积极影响。阐述临床常用的风险评分工具,介绍其主要依赖患者的各项生理健康指标、既往病史等因素以及采用Cox回归模型进行高风险因素快速筛选的能力。回顾不同机器学习模型在急性冠脉综合征患者风险评估中的应用及其在预测长短期不良心血管事件中的特点和能力,并对机器学习算法在医学数据中应用的广阔前景进行展望。Acute coronary syndrome is an acute severe syndrome caused by the decrease of coronary blood flow. It is an important cause of death and long-term severe disability in patients all over the world. Predicting adverse cardiovascular events is of great significance and value for risk screening, early diagnosis and treatment of patients. Machine learning can explore new possibilities and reveal the hidden relationship in the big data of patient information statistics, which will have a positive impact on the auxiliary diagnosis and prognostic analysis of cardiovascular diseases. This paper expounds the commonly used risk scoring tools in clinic, and introduces the factors mainly dependent on patients’ physiological health indicators, past medical history and other factors, as well as the ability of Cox regression model to quickly screen high-risk factors. Review the application of different machine learning models, including random forest, support vector machine and neural network, in assessing the risk of patients with acute coronary syndrome, as well as the relevant characteristics and ability in predicting long-term and short-term adverse cardiovascular events. Finally, it looks forward to the broad prospect of the application of machine learning algorithm in medical data.

关 键 词：急性冠脉综合征 不良心血管事件 机器学习 大数据 辅助诊断 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]