title: Detection of mild Alzheimer's disease and mild cognitive impairment from elderly speech: Binary discrimination using logistic regression.
abstract: 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).
authors.forename: Shohei
authors.initials: S
authors.lastname: Kato
authors.forename: Akira
authors.initials: A
authors.lastname: Homma
authors.forename: Takuto
authors.initials: T
authors.lastname: Sakuma
authors.forename: Munehiro
authors.initials: M
authors.lastname: Nakamura
mesh_terms: D000368:Aged; D000544:Alzheimer Disease; D060825:Cognitive Dysfunction; D006801:Humans; D016015:Logistic Models; D009483:Neuropsychological Tests; D012372:ROC Curve; D013060:Speech