Brain age is an effective biomarker for diagnosing Alzheimer’s disease(AD).Aimed at the issue that the existing brain age detection methods are inconsistent with the biological hypothesis that AD is the accelerated a...Brain age is an effective biomarker for diagnosing Alzheimer’s disease(AD).Aimed at the issue that the existing brain age detection methods are inconsistent with the biological hypothesis that AD is the accelerated aging of the brain,a mutual information—support vector regression(MI-SVR)brain age prediction model is proposed.First,the age deviation is introduced according to the biological hypothesis of AD.Second,fitness function is designed based on mutual information criterion.Third,support vector regression and fitness function are used to obtain the predicted brain age and fitness value of the subjects,respectively.The optimal age deviation is obtained by maximizing the fitness value.Finally,the proposed method is compared with some existing brain age detection methods.Experimental results show that the brain age obtained by the proposed method has better separability,can better reflect the accelerated aging of AD,and is more helpful for improving the diagnostic accuracy of AD.展开更多
基金the Natural Science Foundation of Chongqing(No.cstb2022nscq-msx1575)the Science and Technology Research Program of Chongqing Municipal Education Commission(Nos.KJQN202201512,KJQN202001523 and KJZD-M202101501)+1 种基金the Chongqing University of Science and Technology Research Funding Projects(Nos.CKRC2022019 and CKRC2019042)the Open Foundation of the Chongqing Key Laboratory for Oil and Gas Production Safety and Risk Control(No.cqsrc202113)。
文摘Brain age is an effective biomarker for diagnosing Alzheimer’s disease(AD).Aimed at the issue that the existing brain age detection methods are inconsistent with the biological hypothesis that AD is the accelerated aging of the brain,a mutual information—support vector regression(MI-SVR)brain age prediction model is proposed.First,the age deviation is introduced according to the biological hypothesis of AD.Second,fitness function is designed based on mutual information criterion.Third,support vector regression and fitness function are used to obtain the predicted brain age and fitness value of the subjects,respectively.The optimal age deviation is obtained by maximizing the fitness value.Finally,the proposed method is compared with some existing brain age detection methods.Experimental results show that the brain age obtained by the proposed method has better separability,can better reflect the accelerated aging of AD,and is more helpful for improving the diagnostic accuracy of AD.
文摘我国企业在信息化进程中 ,成功实施的信息系统相对较少 ,多数系统以失败告终 ,其中缺乏一种比较系统全面的战略思想是重要原因。文章详细介绍了 CAL S的产生、发展及应用现状 ,并就其在信息化进程中的重要作用进行了分析 ,指出应该把 CAL S放到国防信息化和国民经济信息化的战略地位 ,刻不容缓地启动 CA LS工程。
