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Detection of mild Alzheimer's disease and mild cognitive impairment from elderly speech: Binary discrimination using logistic regression

机译:从老年人语音中检测轻度阿尔茨海默氏病和轻度认知障碍:使用逻辑回归的二元歧视

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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挖掘方法,用于检测认知障碍SPCIR(基于语音韵律的认知障碍评分),该方法可以使用老年人语音中的韵律符号来区分老年人的轻度认知障碍和轻度阿尔茨海默氏病在问卷测试中。本文提出了使用多元逻辑回归和接收者操作特征(ROC)曲线分析进行模型选择的SPCIR的二元判别模型,并报告了SPCIR对诊断(控制;轻度认知障碍/轻度阿尔茨海默氏病)的敏感性和特异性。

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