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作 者:徐挺玉 景慎旗[1] 王忠民[1] 刘云[1] Xu Tingyu;Jing Shenqi;Wang Zhongmin;Liu Yun(Institute of Medical Informatics and Management,Nanjing Medical University,Information Department,Jiangsu Province Hospital(The First Affiliated Hospital with Nanjing Medical University),Nanjing 210096,Jiangsu Province,China)
机构地区:[1]南京医科大学医学信息学与管理研究所,江苏省人民医院(南京医科大学第一附属医院)信息处,南京210096
出 处:《中国数字医学》2022年第4期1-7,共7页China Digital Medicine
基 金:2020年江苏省科技厅重点研发计划(BE2020721);江苏省经信委升级现代服务业发展专项引导资金投资计划(苏发改服务发〔2019〕1089号);2020工业和信息化部大数据产业发展试点示范项目(2019-243,苏工信数据〔2020〕84号)。
摘 要:随着社会老龄化、经济发展等多种因素影响,慢性非传染性疾病为国民生活带来的巨大危害,面向精准诊疗的慢病防治、数据分析技术研究已成为国内外慢病防治学术界和业界非常关注的焦点,探讨面向精准诊疗的慢病数据分析关键技术。介绍慢性疾病关键技术发展现状、基于本体的模型知识表达、特征提取方法以及相同相关技术。分析常见的面向精准诊疗的慢病数据分析技术,以及具体应用。面向精准诊疗的慢性疾病数据分析关键技术,实现了精确、有效地探索个体间慢病发生的病因和发展过程,识别异常点,找出控制慢病发生,发展的相关因素,进而进行慢病的精准预测、风险判别、及时预警,并辅助临床医生决策,有效降低医疗成本,提高医疗效率和服务质量。With the impact of factors such as social aging and economic development,chronic non-communicable diseases bring enormous harm for the national life.The study on chronic disease prevention and control and data analysis technology for precise diagnosis and treatment has become a focus of the academic circle and industry of chronic disease prevention and control at home and abroad.This paper discusses about key technologies for data analysis of chronic diseases for precise diagnosis and treatment,the current conditions of the development of chronic diseases key technologies,ontology-based model knowledge representation,feature extraction methods,and the same related technologies were introduced.Common chronic disease data analysis technologies for precise diagnosis and treatment and their specific applications were analyzed.With the key technologies for data analysis of chronic diseases for precise diagnosis and treatment,pathogenesis and development process of chronic diseases between individuals are accurately and effectively explored,outliers are identified,and related factors controlling occurrence and development of chronic diseases are found,thus precisely predicting chronic diseases,judging the risks,giving an early warning in a timely manner,helping the clinical doctors to make decisions,effectively reducing medical costs,and improving medical efficiency and service quality.
分 类 号:TP391[自动化与计算机技术—计算机应用技术] R319[自动化与计算机技术—计算机科学与技术]
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