Shaping a data-driven era in dementia care pathway through computational neurology approaches

KongFatt Wong-Lin, Paula McClean, Niamh McCombe, Daman Kaur, Jose Sanchez-Bornot, Paddy Gillespie, Stephen Todd, David Finn, Alok Joshi, Joseph Kane, Bernadette McGuinness

Research output: Contribution to journalReview articlepeer-review

2 Citations (Scopus)
27 Downloads (Pure)

Abstract

Background: Dementia is caused by a variety of neurodegenerative diseases and is associated with a decline in memory and other cognitive abilities, while inflicting an enormous socioeconomic burden. The complexity of dementia and its associated comorbidities presents immense challenges for dementia research and care, particularly in clinical decision-making. Main body: Despite the lack of disease-modifying therapies, there is an increasing and urgent need to make timely and accurate clinical decisions in dementia diagnosis and prognosis to allow appropriate care and treatment. However, the dementia care pathway is currently suboptimal. We propose that through computational approaches, understanding of dementia aetiology could be improved, and dementia assessments could be more standardised, objective and efficient. In particular, we suggest that these will involve appropriate data infrastructure, the use of data-driven computational neurology approaches and the development of practical clinical decision support systems. We also discuss the technical, structural, economic, political and policy-making challenges that accompany such implementations. Conclusion: The data-driven era for dementia research has arrived with the potential to transform the healthcare system, creating a more efficient, transparent and personalised service for dementia.

Original languageEnglish
Article number398
JournalBMC Medicine
Volume18
DOIs
Publication statusPublished - 16 Dec 2020

Bibliographical note

Funding Information:
This project was supported by the European Union’s INTERREG VA Programme, managed by the Special EU Programmes Body (SEUPB; Centre for Personalised Medicine, IVA 5036), with additional support by the Northern Ireland Functional Brain Mapping Project Facility (1303/101154803) and funded by Invest Northern Ireland and the University of Ulster (KW-L), Alzheimer’s Research UK (ARUK) NI Pump Priming (KW-L, PLM, ST, AJ) and Ulster University Research Challenge Fund (KW-L, PLM, ST, AJ). The views and opinions expressed in this paper do not necessarily reflect those of the European Commission or the Special EU Programmes Body (SEUPB).

Publisher Copyright:
© 2020, The Author(s).

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Keywords

  • Alzheimer’s disease
  • Clinical decision support systems
  • Computational modelling
  • Computational neurology
  • Computational neuroscience
  • Data science
  • Dementia
  • Dementia care pathway
  • Healthcare economics

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