{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,4]],"date-time":"2026-11-04T19:47:40Z","timestamp":1793821660113,"version":"4.6.1"},"reference-count":59,"publisher":"Elsevier BV","issue":"7","license":[{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,4,8]],"date-time":"2025-04-08T00:00:00Z","timestamp":1744070400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007165","name":"University of Missouri","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007165","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000062","name":"National Institute of Diabetes and Digestive and Kidney Diseases","doi-asserted-by":"publisher","award":["P30DK092950"],"award-info":[{"award-number":["P30DK092950"]}],"id":[{"id":"10.13039\/100000062","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["The Journal of Prevention of Alzheimer's Disease"],"published-print":{"date-parts":[[2025,8]]},"DOI":"10.1016\/j.tjpad.2025.100169","type":"journal-article","created":{"date-parts":[[2025,4,16]],"date-time":"2025-04-16T07:17:25Z","timestamp":1744787845000},"page":"100169","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":33,"title":["Using machine learning and electronic health record (EHR) data for the early prediction of Alzheimer's Disease and Related Dementias"],"prefix":"10.1016","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9109-3307","authenticated-orcid":false,"given":"Sonia","family":"Akter","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-7671-3275","authenticated-orcid":false,"given":"Zhandi","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4371-4305","authenticated-orcid":false,"given":"Eduardo J.","family":"Simoes","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Praveen","family":"Rao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"7000","key":"10.1016\/j.tjpad.2025.100169_bib0001","doi-asserted-by":"crossref","first-page":"631","DOI":"10.1038\/nature02621","article-title":"Pathways towards and away from Alzheimer's disease","volume":"430","author":"Mattson","year":"2004","journal-title":"Nature"},{"issue":"March","key":"10.1016\/j.tjpad.2025.100169_bib0002","first-page":"1","article-title":"Early-stage Alzheimer's disease prediction using machine learning models","volume":"10","author":"Kavitha","year":"2022","journal-title":"Front Public Heal"},{"issue":"1","key":"10.1016\/j.tjpad.2025.100169_bib0003","doi-asserted-by":"crossref","first-page":"1","DOI":"10.5114\/fn.2013.34190","article-title":"Molecular mechanisms of neuropathological changes in Alzheimer's disease: a review","volume":"51","author":"\u0160er\u00fd","year":"2013","journal-title":"Folia Neuropathol"},{"issue":"4","key":"10.1016\/j.tjpad.2025.100169_bib0004","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1016\/j.jalz.2018.02.018","article-title":"NIA-AA Research Framework: toward a biological definition of Alzheimer's disease","volume":"14","author":"Jack","year":"2018","journal-title":"Alzheimer's Dement [Internet]"},{"issue":"1","key":"10.1016\/j.tjpad.2025.100169_bib0005","first-page":"1","article-title":"\u03b2-amyloid and tau drive early Alzheimer's disease decline while glucose hypometabolism drives late decline","volume":"3","author":"Hammond","year":"2020","journal-title":"Commun Biol [Internet]"},{"issue":"5","key":"10.1016\/j.tjpad.2025.100169_bib0006","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3390\/ijms22052761","article-title":"Machine learning and novel biomarkers for the diagnosis of alzheimer's disease","volume":"22","author":"Chang","year":"2021","journal-title":"Int J Mol Sci"},{"issue":"3","key":"10.1016\/j.tjpad.2025.100169_bib0007","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1016\/j.jalz.2011.03.003","article-title":"Toward defining the preclinical stages of Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease","volume":"7","author":"Sperling","year":"2011","journal-title":"Alzheimer's Dement"},{"issue":"4","key":"10.1016\/j.tjpad.2025.100169_bib0008","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1016\/S1474-4422(13)70044-9","article-title":"Amyloid \u03b2 deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer's disease: a prospective cohort study","volume":"12","author":"Villemagne","year":"2013","journal-title":"Lancet Neurol [Internet]"},{"issue":"3","key":"10.1016\/j.tjpad.2025.100169_bib0009","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1016\/j.jalz.2011.03.005","article-title":"The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease","volume":"7","author":"McKhann","year":"2011","journal-title":"Alzheimer's Dement"},{"issue":"3","key":"10.1016\/j.tjpad.2025.100169_bib0010","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1111\/joim.12190","article-title":"Mild cognitive impairment: a concept in evolution","volume":"275","author":"Petersen","year":"2014","journal-title":"J Intern Med"},{"issue":"3","key":"10.1016\/j.tjpad.2025.100169_bib0011","doi-asserted-by":"crossref","first-page":"270","DOI":"10.1016\/j.jalz.2011.03.008","article-title":"The diagnosis of mild cognitive impairment due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease","volume":"7","author":"Albert","year":"2011","journal-title":"Alzheimer's Dement"},{"issue":"4","key":"10.1016\/j.tjpad.2025.100169_bib0012","doi-asserted-by":"crossref","first-page":"700","DOI":"10.1002\/alz.12638","article-title":"2022 Alzheimer's disease facts and figures","volume":"18","year":"2022","journal-title":"Alzheimer's Dement"},{"issue":"4","key":"10.1016\/j.tjpad.2025.100169_bib0013","doi-asserted-by":"crossref","first-page":"1598","DOI":"10.1002\/alz.13016","article-title":"2023 Alzheimer's disease facts and figures","volume":"19","year":"2023","journal-title":"Alzheimer's Dement"},{"issue":"14","key":"10.1016\/j.tjpad.2025.100169_bib0014","doi-asserted-by":"crossref","first-page":"1326","DOI":"10.1056\/NEJMsa1204629","article-title":"Monetary costs of dementia in the United States","volume":"368","author":"Hurd","year":"2013","journal-title":"N Engl J Med"},{"key":"10.1016\/j.tjpad.2025.100169_bib0015","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.ijmedinf.2017.07.002","article-title":"Advancing Alzheimer's research: a review of big data promises","volume":"106","author":"Zhang","year":"2017","journal-title":"Int J Med Inform [Internet]"},{"issue":"1","key":"10.1016\/j.tjpad.2025.100169_bib0016","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.jalz.2016.07.150","article-title":"The worldwide costs of dementia 2015 and comparisons with 2010","volume":"13","author":"Wimo","year":"2017","journal-title":"Alzheimer's Dement"},{"issue":"4","key":"10.1016\/j.tjpad.2025.100169_bib0017","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1186\/alzrt269","article-title":"Alzheimer's disease drug-development pipeline: few candidates, frequent failures","volume":"6","author":"Cummings","year":"2014","journal-title":"Alzheimers Res Ther"},{"issue":"1","key":"10.1016\/j.tjpad.2025.100169_bib0018","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1002\/alz.12372","article-title":"State-of-the-art of lumbar puncture and its place in the journey of patients with Alzheimer's disease","volume":"18","author":"Hampel","year":"2022","journal-title":"Alzheimer's Dement"},{"issue":"3","key":"10.1016\/j.tjpad.2025.100169_bib0019","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1002\/alz.12068","article-title":"Alzheimer's disease facts and figures 2020","volume":"16","year":"2020","journal-title":"Alzheimer's Dement"},{"key":"10.1016\/j.tjpad.2025.100169_bib0020","doi-asserted-by":"crossref","unstructured":"Barthold D., Joyce G., Ferido P., Drabo E.F., Marcum Z.A., Gray S.L., et al. Pharmaceutical treatment for Alzheimer \u2019 s disease and related dementias: utilization and disparities. 2020;76:579\u201389.","DOI":"10.3233\/JAD-200133"},{"issue":"1","key":"10.1016\/j.tjpad.2025.100169_bib0021","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1177\/1756285612461679","article-title":"Current and future treatments for Alzheimer's disease","volume":"6","author":"Yiannopoulou","year":"2013","journal-title":"Ther Adv Neurol Disord"},{"issue":"3","key":"10.1016\/j.tjpad.2025.100169_bib0022","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1002\/alz.12328","article-title":"Alzheimer's disease facts and figures 2021","volume":"17","year":"2021","journal-title":"Alzheimer's Dement"},{"key":"10.1016\/j.tjpad.2025.100169_bib0023","first-page":"1","article-title":"Early prediction of Alzheimer's disease and related dementias using real-world electronic health records","author":"Li","year":"2023","journal-title":"Alzheimer's Dement"},{"issue":"3","key":"10.1016\/j.tjpad.2025.100169_bib0024","doi-asserted-by":"crossref","first-page":"685","DOI":"10.3233\/JAD-131928","article-title":"Multivariate data analysis and machine learning in Alzheimer's disease with a focus on structural magnetic resonance imaging","volume":"41","author":"Falahati","year":"2014","journal-title":"J Alzheimer's Dis"},{"key":"10.1016\/j.tjpad.2025.100169_bib0025","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.neuroimage.2016.02.079","article-title":"Single subject prediction of brain disorders in neuroimaging: promises and pitfalls","volume":"145","author":"Xuefeng","year":"2017","journal-title":"Neuroimage"},{"issue":"1","key":"10.1016\/j.tjpad.2025.100169_bib0026","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1093\/jamia\/ocw042","article-title":"Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review","volume":"24","author":"Goldstein","year":"2017","journal-title":"J Am Med Inform Assoc"},{"issue":"1","key":"10.1016\/j.tjpad.2025.100169_bib0027","article-title":"Machine learning prediction of incidence of Alzheimer's disease using large-scale administrative health data","volume":"3","author":"Park","year":"2020","journal-title":"npj Digit Med [Internet]"},{"key":"10.1016\/j.tjpad.2025.100169_bib0028","doi-asserted-by":"crossref","first-page":"918","DOI":"10.1016\/j.trci.2019.10.006","article-title":"Machine learning models to predict onset of dementia: a label learning approach","volume":"5","author":"Nori","year":"2019","journal-title":"Alzheimer's Dement Transl Res Clin Interv"},{"issue":"23","key":"10.1016\/j.tjpad.2025.100169_bib0029","doi-asserted-by":"crossref","first-page":"2668","DOI":"10.1016\/j.jacc.2018.03.521","article-title":"Artificial intelligence in cardiology","volume":"71","author":"Johnson","year":"2018","journal-title":"J Am Coll Cardiol"},{"issue":"1","key":"10.1016\/j.tjpad.2025.100169_bib0030","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12911-019-0801-4","article-title":"Predicting factors for survival of breast cancer patients using machine learning techniques","volume":"19","author":"Ganggayah","year":"2019","journal-title":"BMC Med Inform Decis Mak"},{"issue":"1","key":"10.1016\/j.tjpad.2025.100169_bib0031","doi-asserted-by":"crossref","DOI":"10.1186\/s41747-019-0109-2","article-title":"Machine learning applications in prostate cancer magnetic resonance imaging","volume":"3","author":"Cuocolo","year":"2019","journal-title":"Eur Radiol Exp"},{"issue":"10248","key":"10.1016\/j.tjpad.2025.100169_bib0032","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1016\/S0140-6736(20)30367-6","article-title":"Dementia prevention, intervention, and care: 2020 report of the Lancet Commission","volume":"396","author":"Livingston","year":"2020","journal-title":"Lancet."},{"key":"10.1016\/j.tjpad.2025.100169_bib0033","first-page":"35","article-title":"What is cognitive reserve? Theory and research application of the reserve concept","author":"Stern","year":"2017","journal-title":"Psychol Aging"},{"issue":"10","key":"10.1016\/j.tjpad.2025.100169_bib0034","doi-asserted-by":"crossref","first-page":"1017","DOI":"10.1016\/S1474-4422(14)70172-3","article-title":"Connections between sleep and cognition in older adults","volume":"13","author":"Yaffe","year":"2014","journal-title":"Lancet Neurol"},{"issue":"3","key":"10.1016\/j.tjpad.2025.100169_bib0035","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1001\/jamainternmed.2014.7663","article-title":"Cumulative use of strong anticholinergics and incident dementia: a prospective cohort study","volume":"175","author":"Gray","year":"2015","journal-title":"JAMA Intern Med"},{"issue":"7","key":"10.1016\/j.tjpad.2025.100169_bib0036","doi-asserted-by":"crossref","DOI":"10.1001\/jamanetworkopen.2019.6972","article-title":"Development and validation of a deep learning algorithm for mortality prediction in selecting patients with dementia for earlier palliative care interventions","volume":"2","author":"Wang","year":"2019","journal-title":"JAMA Netw Open"},{"issue":"5","key":"10.1016\/j.tjpad.2025.100169_bib0037","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1214\/aos\/1013203450","article-title":"Greedy function approximation: a gradient boosting machine author [(s): jerome H. Friedmansourcee:thee Annals of Statistics,publishedd by: institute of Mathematical Statisticsstablee URL","volume":"29","author":"Friedman","year":"2001","journal-title":"Ann Stat [Internet]"},{"key":"10.1016\/j.tjpad.2025.100169_bib0038","first-page":"3147","article-title":"LightGBM: a highly efficient gradient boosting decision tree","author":"Ke","year":"2017","journal-title":"Adv Neural Inf Process Syst"},{"key":"10.1016\/j.tjpad.2025.100169_bib0039","doi-asserted-by":"crossref","unstructured":"Chen T., Guestrin C. XGBoost: a scalable tree boosting system. Proc ACM SIGKDD Int Conf Knowl Discov Data Min. 2016;13-17-Augu:785\u201394.","DOI":"10.1145\/2939672.2939785"},{"key":"10.1016\/j.tjpad.2025.100169_bib0040","doi-asserted-by":"crossref","unstructured":"R.A. Fishers, Sc.D. FRS. The use of multiple measurements in taxonomic problems. 1954;1(1):1\u20138. Disponible a: https:\/\/doi.org\/10.1111\/j.1469-1809.1936.tb02137.x.","DOI":"10.1111\/j.1469-1809.1936.tb02137.x"},{"issue":"1","key":"10.1016\/j.tjpad.2025.100169_bib0041","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1006\/jcss.1997.1504","article-title":"A decision-theoretic generalization of on-line learning and an application to boosting","volume":"55","author":"Freund","year":"1997","journal-title":"J Comput Syst Sci"},{"key":"10.1016\/j.tjpad.2025.100169_bib0042","unstructured":"National Patient-Centered Outcomes Research Network. Common data model (CDM) specification, version 3 . 0 1 [Internet]. 2015. p. 1\u201387. Disponible a: https:\/\/pcornet.org\/data\/."},{"key":"10.1016\/j.tjpad.2025.100169_bib0043","unstructured":"U.S. Food and Drug Administration. FDA approves first drug to treat agitation symptoms associated with dementia due to Alzheimer's Disease [Internet]. 2023. Disponible a: https:\/\/www.fda.gov\/news-events\/press-announcements\/fda-approves-first-drug-treat-agitation-symptoms-associated-dementia-due-alzheimers-disease."},{"issue":"6","key":"10.1016\/j.tjpad.2025.100169_bib0044","first-page":"718","article-title":"Summary of the evidence on modifiable risk factors for cognitive decline and dementia: a population-based perspective","volume":"11","author":"Matthew","year":"2015","journal-title":"Alzheimer's Dement Diagnosis, Assess Dis Monit"},{"issue":"2","key":"10.1016\/j.tjpad.2025.100169_bib0045","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1097\/00001573-199903000-00014","article-title":"A review of the Sixth Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure","volume":"14","author":"Schwartz","year":"1999","journal-title":"Curr Opin Cardiol [Internet]"},{"issue":"1","key":"10.1016\/j.tjpad.2025.100169_bib0046","doi-asserted-by":"crossref","DOI":"10.1186\/s13195-021-00900-w","article-title":"Machine learning methods for predicting progression from mild cognitive impairment to Alzheimer's disease dementia: a systematic review","volume":"13","author":"Grueso","year":"2021","journal-title":"Alzheimer's Res Ther"},{"issue":"OCT","key":"10.1016\/j.tjpad.2025.100169_bib0047","first-page":"1","article-title":"Random forest algorithm for the classification of neuroimaging data in Alzheimer's disease: a systematic review","volume":"9","author":"Sarica","year":"2017","journal-title":"Front Aging Neurosci"},{"issue":"3","key":"10.1016\/j.tjpad.2025.100169_bib0048","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/jamiaopen\/ooab052","article-title":"Machine learning for modeling the progression of Alzheimer disease dementia using clinical data: a systematic literature review","volume":"4","author":"Kumar","year":"2021","journal-title":"JAMIA Open"},{"issue":"7","key":"10.1016\/j.tjpad.2025.100169_bib0049","doi-asserted-by":"crossref","DOI":"10.3390\/life12071097","article-title":"An intelligent learning system for unbiased prediction of dementia based on autoencoder and adaboost ensemble learning","volume":"12","author":"Javeed","year":"2022","journal-title":"Life"},{"issue":"3","key":"10.1016\/j.tjpad.2025.100169_bib0050","first-page":"426","article-title":"A unified approach to interpreting model predictions","volume":"16","author":"Lundberg","year":"2017","journal-title":"Nips"},{"key":"10.1016\/j.tjpad.2025.100169_bib0051","unstructured":"Akter S., Liu Z., Simoes E.J., Rao P. Machine learning for early prediction of Alzheimer's disease and related dementias using electronic health record (EHR) data. En Pittsburg, Penn: American Medical Informatics Association (AMIA) Informatics Summit, March 2025, Pittsburgh, PA (Poster)."},{"issue":"12","key":"10.1016\/j.tjpad.2025.100169_bib0052","doi-asserted-by":"crossref","first-page":"723","DOI":"10.1038\/nrn3114","article-title":"Neurovascular pathways to neurodegeneration in Alzheimer's disease and other disorders","volume":"12","author":"Zlokovic","year":"2011","journal-title":"Nat Rev Neurosci"},{"issue":"1","key":"10.1016\/j.tjpad.2025.100169_bib0053","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1002\/ana.21915","article-title":"Dementia incidence continues to increase with age in the oldest old the 90+ study","volume":"67","author":"Corrada","year":"2010","journal-title":"Ann Neurol"},{"issue":"11","key":"10.1016\/j.tjpad.2025.100169_bib0054","doi-asserted-by":"crossref","first-page":"1006","DOI":"10.1016\/S1474-4422(12)70191-6","article-title":"Cognitive reserve in ageing and Alzheimer's disease","volume":"11","author":"Stern","year":"2012","journal-title":"Lancet Neurol [Internet]"},{"issue":"11","key":"10.1016\/j.tjpad.2025.100169_bib0055","doi-asserted-by":"crossref","DOI":"10.1093\/sleep\/zsac216","article-title":"Insomnia and subjective cognitive decline in older adults: avenues for continued investigation and potential intervention","volume":"45","author":"Dzierzewski","year":"2022","journal-title":"Sleep"},{"issue":"26","key":"10.1016\/j.tjpad.2025.100169_bib0056","article-title":"Sleep disturbance and cognition in the elderly: a narrative review","volume":"2","author":"Ni","year":"2024","journal-title":"Anesthesiol Perioper Sci [Internet]"},{"issue":"1","key":"10.1016\/j.tjpad.2025.100169_bib0057","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0087095","article-title":"Diabetes mellitus and the risk of Alzheimer's disease: a nationwide population-based study","volume":"9","author":"Huang","year":"2014","journal-title":"PLoS One"},{"key":"10.1016\/j.tjpad.2025.100169_bib0058","article-title":"Metabolic and immune system dysregulation: unraveling the connections between Alzheimer \u2019 s Disease, diabetes","author":"Doroszkiewicz","year":"2024","journal-title":"Inflam Bowel Dis, Rheumatoid Arthri"},{"issue":"17","key":"10.1016\/j.tjpad.2025.100169_bib0059","doi-asserted-by":"crossref","DOI":"10.3390\/ijms23179540","article-title":"Dysfunctional glucose metabolism in Alzheimer's Disease onset and potential pharmacological interventions","volume":"23","author":"Kumar","year":"2022","journal-title":"Int J Mol Sci"}],"container-title":["The Journal of Prevention of Alzheimer's Disease"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2274580725001141?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2274580725001141?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T20:57:21Z","timestamp":1785963441000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2274580725001141"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8]]},"references-count":59,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2025,8]]}},"alternative-id":["S2274580725001141"],"URL":"https:\/\/doi.org\/10.1016\/j.tjpad.2025.100169","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2024.12.09.24318740","asserted-by":"object"}]},"ISSN":["2274-5807"],"issn-type":[{"value":"2274-5807","type":"print"}],"subject":[],"published":{"date-parts":[[2025,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Using machine learning and electronic health record (EHR) data for the early prediction of Alzheimer's Disease and Related Dementias","name":"articletitle","label":"Article Title"},{"value":"The Journal of Prevention of Alzheimer's Disease","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.tjpad.2025.100169","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Authors. Published by Elsevier Masson SAS on behalf of SERDI Publisher.","name":"copyright","label":"Copyright"}],"article-number":"100169"}}