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基于特征自动识别的心肌梗死关键因素挖掘研究 被引量：1

Study on the Mining of Key Factors of Myocardial Infarction Based on the Automatic Feature Recognition
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摘要 利用人工智能技术,基于患者既往就诊数据进行机器学习相关算法分析,建立心肌梗死疾病特征自动识别模型,通过特征挖掘找出关键和主要致病因素,为医生提供定性或定量辅助诊断意见。 Artificial Intelligence(AI)technology is used to analyze the Machine Learning(ML)algorithm based on the patients’previous medical data,and an automatic recognition model for disease features of myocardial infarction is built.The key and main pathogenic factors are found through feature mining to provide qualitative or quantitative auxiliary diagnosis advices for doctors.
作者 王颖晶 郑涛 陈珊黎 邵维君 韩刚 丁粉华 WANG Yingjing;ZHENG Tao;CHEN Shanli;SHAO Weijun;HAN Gang;DING Fenhua(Information Center,Renji Hospital,Shanghai Jiao Tong University School of Medicine,Shanghai 200127,China)
机构地区 上海交通大学医学院附属仁济医院信息中心
出处 《医学信息学杂志》 CAS 2022年第1期54-58,共5页 Journal of Medical Informatics
基金 上海市信息化发展专项资金项目“面向仁济医院医联体的专病临床科研智能辅助决策平台建设”(项目编号:201901007)。
关键词 心肌梗死 机器学习 特征重要性 myocardial infarction Machine Learning(ML) feature importance
分类号 R-056 [医药卫生]
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医学信息学杂志
2022年 第1期

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