Computational Neurology: Computational Modeling Approaches in Dementia

KongFatt Wong-Lin, Jose Sanchez Bornot, Niamh McCombe, Daman Kaur, Paula McClean, Xin Zou, Vahab Youssofzadeh, Xuemei Ding, Magda Bucholc, Su Yang, Girijesh Prasad, Damien Coyle, Liam Maguire, Haiying / HY Wang, H. Wang, Nadim Atiya, Alok Joshi

Research output: Chapter or section in a book/report/conference proceedingChapter or section

3 Citations (SciVal)

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.
Original languageEnglish
Title of host publicationSystems Medicine
Subtitle of host publicationIntegrative, Qualitative and Computational Approaches
EditorsOlaf Wolkenhauer
Place of PublicationU.S.A.
PublisherElsevier Academic Press Inc
Pages81-89
Number of pages9
ISBN (Electronic)9780128160787
ISBN (Print)9780128160770
Publication statusPublished - 28 Aug 2020

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