急性冠脉综合征风险预测模型的方法学探讨  

Approach to the Method of Risk Prediction Model for Acute Coronary Syndrome

作　　者：连扬鹏[1] LIAN Yangpeng(Department of Information Management,Fujian Provincial Hospital,Fuzhou,China,350001)

机构地区：[1]福建省立医院信息管理中心,福州350001

出　　处：《福建电脑》2021年第12期60-63,共4页Journal of Fujian Computer

基　　金：福建省卫生健康委青年科研课题(No.2019-1-1)资助。

摘　　要：为了降低急性冠状动脉综合征的疾病发生率、改善患者预后和疾病负担,早期识别和预测急性冠状动脉综合征的发生风险是有效手段。通过分析急性冠状动脉综合征风险预测模型的应用进展情况,建立专病数据库,构建风险预测模型。对传统回归模型和多种机器学习方法进行分别建模,通过相关指标综合评价比较模型,可选择最优预测模型。预测模型可在临床实践中进行前瞻性验证,并尝试在临床上推广,为开展临床研究奠定理论基础。In order to reduce the incidence of acute coronary syndrome and improve patient prognosis and disease burden,early identification and prediction of the risk of acute coronary syndrome is an effective means.By analyzing the application progress of the acute coronary syndrome risk prediction model,establishing a special disease database and constructing a risk prediction model.Model the traditional regression model and multiple machine learning methods separately,comprehensively evaluate and compare models through related indicators,and choose the best predictive model.The predictive model can be prospectively verified in clinical practice,and will try to be promoted in clinical practice to lay a theoretical foundation for clinical research.

关 键 词：机器学习 急性冠脉综合征 风险预测模型 人工智能 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]