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Predicting incident dementia in cerebral small vessel disease : comparison of machine learning and traditional statistical models

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dc.contributor.authorLi, Rui
dc.contributor.authorHarshfield, Eric L.
dc.contributor.authorBell, Steven
dc.contributor.authorBurkhart, Michael
dc.contributor.authorTuladhar, Anil M.
dc.contributor.authorHilal, Saima
dc.contributor.authorTozer, Daniel J.
dc.contributor.authorChappell, Francesca M.
dc.contributor.authorMakin, Stephen D.J.
dc.contributor.authorLo, Jessica W.
dc.contributor.authorWardlaw, Joanna M.
dc.contributor.authorde Leeuw, Frank Erik
dc.contributor.authorChen, Christopher
dc.contributor.authorKourtzi, Zoe
dc.contributor.authorMarkus, Hugh S.
dc.contributor.institutionUniversity of Aberdeen.Other Applied Health Sciencesen
dc.date.accessioned2023-09-25T13:32:01Z
dc.date.available2023-09-25T13:32:01Z
dc.date.issued2023
dc.descriptionFunding Information: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was funded by a British Heart Foundation (BHF) programme grant [grant number RG/F/22/110052 ] and infrastructural support was provided by the Cambridge British Heart Foundation Centre of Research Excellence [grant number RE/18/1/34212 ] and the Cambridge University Hospitals NIHR Biomedical Research Centre [grant number BRC-1215–20014 ]. Funding Information: HSM is supported by an NIHR Senior Investigator Award, and a number of peer reviewed funders including Medical Research Council, EU, Alzheimer's Society, Stroke Association, BHF. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. RL is supported by a PhD scholarship awarded by Trinity College, University of Cambridge. ELH is supported by Cambridge BHF Centre of Research Excellence [grant number RE/18/1/34212 ]; Alzheimer's Society [grant number AS-RF-21–017 ]; BHF programme grant [grant number RG/F/22/110052 ]; Cambridge NIHR Biomedical Research Centre [grant number BRC-1215–20014 ]. SB is supported by BHF . AMT is supported by Dutch Heart Foundation [grant number 2016T044 ]. Wellcome Trust [grant number 081589 ] provided initial funding for SCANS study. SDJM is supported by Wellcome Trust [grant number WT088134/Z/09/A ]. JMW is supported by Wellcome Trust , Row Fogo Trust , and Medical Research Council . CC is supported by National Medical Research Council of Singapore. ZK is supported by Wellcome Trust and Alan Turing Institute.en
dc.description.statusPeer revieweden
dc.format.extent8
dc.format.extent2178961
dc.identifier281350252
dc.identifier85ad18ca-3b11-4bc2-9fec-6a28af05b5a9
dc.identifier85167790782
dc.identifier37593075
dc.identifier.citationLi, R, Harshfield, E L, Bell, S, Burkhart, M, Tuladhar, A M, Hilal, S, Tozer, D J, Chappell, F M, Makin, S D J, Lo, J W, Wardlaw, J M, de Leeuw, F E, Chen, C, Kourtzi, Z & Markus, H S 2023, 'Predicting incident dementia in cerebral small vessel disease : comparison of machine learning and traditional statistical models', Cerebral Circulation - Cognition and Behavior, vol. 5, 100179. https://doi.org/10.1016/j.cccb.2023.100179en
dc.identifier.doi10.1016/j.cccb.2023.100179
dc.identifier.issn2666-2450
dc.identifier.otherORCID: /0000-0001-8701-9043/work/142977961
dc.identifier.urihttps://hdl.handle.net/2164/21738
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85167790782&partnerID=8YFLogxKen
dc.identifier.vol5en
dc.language.isoeng
dc.relation.ispartofCerebral Circulation - Cognition and Behavioren
dc.subjectCerebral small vessel diseaseen
dc.subjectDementiaen
dc.subjectMachine learningen
dc.subjectPredictionen
dc.subjectR Medicineen
dc.subjectNeurologyen
dc.subjectCognitive Neuroscienceen
dc.subjectClinical Neurologyen
dc.subjectBiological Psychiatryen
dc.subjectBehavioral Neuroscienceen
dc.subject.lccRen
dc.titlePredicting incident dementia in cerebral small vessel disease : comparison of machine learning and traditional statistical modelsen
dc.typeJournal articleen

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