Biometric data and machine learning methods in the diagnosis and monitoring of neurodegenerative diseases: a review

Autor:	I.A. Hodashinsky, K.S. Sarin, M.B. Bardamova, M.O. Svetlakov, A.O. Slezkin, N.P. Koryshev
Jazyk:	English<br />Russian
Rok vydání:	2022
Předmět:	non-invasive diagnostic methods neurodegenerative diseases biometric signal processing machine learning Information theory Q350-390 Optics. Light QC350-467
Zdroj:	Компьютерная оптика, Vol 46, Iss 6, Pp 988-1019 (2022)
Druh dokumentu:	article
ISSN:	2412-6179 0134-2452
DOI:	10.18287/2412-6179-CO-1134
Popis:	A review of noninvasive biometric methods for detecting and predicting neurodegenerative diseases is presented. An analysis of various modalities used to diagnose and monitor diseases is given. Such modalities as handwritten data, electroencephalography, speech, gait, eye movement, as well as the use of compositions of these modalities are considered. A detailed analysis of modern methods and solutions based on machine learning is conducted. Data sets, preprocessing methods, machine learning models, and accuracy estimates for disease diagnosis are presented. In the conclusion current open problems and future prospects of research in this direction are considered.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/d8e1089492c54ff9bd82090a6111834f Zobrazit plný text záznamu View record in DOAJ