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 in Book/Report/Conference proceedingChapterpeer-review

3 Citations (Scopus)


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: Integrative, Qualitative and Computational Approaches
EditorsOlaf Wolkenhauer
PublisherElsevier Inc.
Number of pages9
ISBN (Electronic)9780128160787
ISBN (Print)9780128160770
Publication statusPublished (in print/issue) - 24 Aug 2020


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