Shaping a data-driven era in dementia care pathway through computational neurology approaches
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Shaping a data-driven era in dementia care pathway through computational neurology approaches KongFatt Wong-Lin1* , Paula L. McClean2, Niamh McCombe1, Daman Kaur2, Jose M. Sanchez-Bornot1, Paddy Gillespie3, Stephen Todd4, David P. Finn5, Alok Joshi1, Joseph Kane6 and Bernadette McGuinness6
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. Keywords: Dementia, Alzheimer’s disease, Dementia care pathway, Data science, Computational neurology, Computational modelling, Computational neuroscience, Healthcare economics, Clinical decision support systems
Background Dementia refers to a clinical syndrome distinct from physiological ageing, caused by one or more pathological processes and characterised by progressive impairment in cognition and everyday functioning [1]. Alzheimer’s disease (AD), typically characterised by impairment in memory, is the most common subtype of dementia, constituting 60–70% of the cases [1]. AD can be categorised * Correspondence: [email protected] 1 Intelligent Systems Research Centre, School of Computing, Engineering and Intelligent Systems, Ulster University, Magee Campus, Londonderry, Northern Ireland, UK Full list of author information is available at the end of the article
as familial AD (with a family history of the disease and early AD onset) and sporadic AD, with the latter overwhelmingly being the most common type [2]. AD may coexist with pathological processes characteristic of other common dementia subtypes such as vascular dementia, frontotemporal dementia and Lewy body dementia [1]. Further, there may also be co-morbidities with other illnesses such as epilepsy [3]. To add to the complexity, the prodromal stages, or mild cognitive impairment (MCI), associa
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