Improved Detection of Mild Cognitive Impairment from Temporal Language Markers Using Subject‐invariant Representation Learning using I‐CONECT data

Abstract

Background: Mild Cognitive Impairment (MCI) is the prodromal stage of Alzheimer's disease. Early detection of MCI is essential for effective intervention and treatment. Recent studies have shown that linguistic marker is a promising and cost‐effective approach to identify MCI.