Computational neurology: computational modeling approaches in Dementia

Wong-Lin, KongFatt, Sanchez-Bornot, Jose M., McCombe, Niamh, Kaur, Daman, McClean, Paula L., Zou, Xin, Youssofzadeh, Vahab, Ding, Xuemei, Bucholc, Magda, Yang, Su ORCID: https://orcid.org/0000-0002-6618-7483, Prasad, Girijesh, Coyle, Damien, Maguire, Liam P., Wang, Haiying, Wang, Hui, Atiya, Nadim A.A. and Joshi, Alok (2020) Computational neurology: computational modeling approaches in Dementia. arXiv.org. (Submitted)

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Abstract

Dementia is a collection of symptoms associated with impaired cognition and impedes everyday normal functioning. Dementia, with Alzheimer’s disease constituting its most common type, is highly complex in terms of etiology and pathophysiology. A more quantitative or computational attitude towards dementia research, or more generally in neurology, is becoming necessary – Computational Neurology. We provide a focused review of some computational approaches that have been developed and applied to the study of dementia, particularly Alzheimer’s disease. Both mechanistic modeling and data-driven, including AI or machine learning, approaches are discussed. Linkage to clinical decision support systems for dementia diagnosis will also be discussed.

Item Type: Article
Subjects: Medicine and health > Clinical medicine > Dementia
Computing
Depositing User: Su Yang
Date Deposited: 07 Jun 2021 09:56
Last Modified: 07 Jun 2021 09:57
URI: http://repository.uwl.ac.uk/id/eprint/7939

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