NLP Based Automated Screening Tools for Alzheimer’s Disease

Detta är en Kandidat-uppsats från KTH/Datavetenskap

Författare: August Erséus; Ted Strömfelt; [2022]

Nyckelord: alzheimer’s; dementia; digital; screening; nlp;

Sammanfattning: Severely life-impairing and often lethal dementia illnesses such as Alzheimer’s disease are of the greatest medical interest. And while a cure might yet be years in the future, there are immense benefits to gain from detecting disease debut as early as possible, from both an individual and a societal perspective. In this study we explore new approaches to Alzheimer’s screening, utilizing the recent technology leaps within natural language processing and automated speech recognition. We propose a digital, mobile application based platform for psychometric data collection that can be used by patients and research participants in a non-clinical environment. In particular, we implement automated versions of two well-recognized psychometric tests for Alzheimer’s screening: the Verbal Learning Test and the Story Recall Task. We perform a qualitative evaluation of results from 46 sessions of these tests, as well as a semi-structured interview with a clinician, and find automated psychometric tools promising for future endeavors within Alzheimer’s screening, but that the method has inherent difficulties that needs to be counteracted. We also discuss the potential economic upsides with automating parts of the screening and diagnosis processes for dementia related diseases, and conclude that there are massive savings to make – up to 600 million SEK yearly in Sweden alone.

  HÄR KAN DU HÄMTA UPPSATSEN I FULLTEXT. (följ länken till nästa sida)