Linguistic-Based Mild Cognitive Impairment Detection Using Informative Loss

This paper presents a deep learning method using Natural Language Processing (NLP) techniques, to distinguish between Mild Cognitive Impairment (MCI) and Normal Cognitive (NC) conditions in older adults. We propose a framework that analyzes transcripts generated from video interviews collected within the I-CONECT study project, a randomized controlled trial aimed at improving cognitive functions through video chats. Our proposed NLP framework consists of two Transformer-based modules, namely Sentence Embedding (SE) and Sentence Cross Attention (SCA). First, the SE module captures …

cognitive cs.cl cs.lg deep learning detection framework generated interviews language language processing loss natural natural language natural language processing nlp normal paper processing project study transcripts video