Analysis of Speech Features in Alzheimer's Disease with Machine Learning: A Case-Control Study.

Background: Changes in the speech and language of patients with Alzheimer's disease (AD) have been reported. Using machine learning to characterize these irregularities may contribute to the early, non-invasive diagnosis of AD.

Methods: We conducted cognitive function assessments, including the Mini-Mental State Examination, with 83 patients with AD and 75 healthy elderly participants, and recorded pre- and post-assessment conversations to evaluate participants' speech.