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Detection of Mild Alzheimer's Disease and Mild Cognitive Impairment from Elderly Speech: binary discrimination using logistic regression

机译:检测轻度阿尔茨海默氏病和老年人语言的轻度认知障碍:使用Logistic回归的二进制鉴别

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In this research, we have developed a novel data-mining approach for detection of cognitive impairment, SPCIR (Speech Prosody-Based Cognitive Impairment Rating), which can discriminate between mild cognitive impairment and mild Alzheimer's disease from elderly using prosodic sign extracted from elderly speech during questionnaire test. This paper proposes a binary discrimination model of SPCIR using multivariate logistic regression and model selection using receiver operating characteristic (ROC) curve analysis, and reports the sensitivity and specificity of SPCIR for diagnosis (control; mild cognitive impairment/mild Alzheimer's disease).
机译:在这项研究中,我们开发了一种新的数据采矿方法,用于检测认知障碍,SPCIR(基于语音韵律的认知障碍等级),可以区分轻度认知障碍和来自老年人的韵律符号从老年言语中提取的韵律症状在调查问卷测试期间。本文提出了使用多变量逻辑回归和模型选择使用接收器操作特征(ROC)曲线分析的模型选择的二进制辨别模型,并报告SPCIR进行诊断的敏感性和特异性(对照;轻度认知障碍/轻度阿尔茨海默病)。

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