ArticlemedRxiv : the preprint server for health sciences2025
Predicting Alzheimer's Disease Diagnosis, a Decade or more Years before Onset using the Electronic Health Record and Random Forest Machine Learning Models.
Sanya B Taneja, Richard D Boyce, Scott A Malec, Steven M Albert, C Elizabeth Shaaban, Arthur S Levine, Paul Munro, Jiang Bian, Jie Xu, Demetrius Maraganore and 4 more
Abstract readPreprint
In one paragraphArticle in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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2 · The registryThe trial behind it
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5 · Who and what moneyAuthors and funding
14 authors.
Sanya B TanejaIntelligent Systems Program, University of Pittsburgh, 6127 Sennott Square 210 South Bouquet Street Pittsburgh, PA 15260.ORCID 0000-0003-1707-1617 Richard D BoyceIntelligent Systems Program, University of Pittsburgh, 6127 Sennott Square 210 South Bouquet Street Pittsburgh, PA 15260.ORCID 0000-0002-2993-2085 Scott A MalecDivision of Translational Informatics, University of New Mexico, 1 University of New Mexico Albuquerque, New Mexico 87131 MSC09-5025.ORCID 0000-0003-1696-1781 Steven M AlbertDepartment of Behavioral and Community Health Sciences, University of Pittsburgh, 130 De Soto Street Pittsburgh, PA 15261 USA.ORCID 0000-0001-6786-9956 C Elizabeth ShaabanDepartment of Health Promotion and Development, School of Nursing, 3500 Victoria Street, Victoria Building Suite 440, Pittsburgh, PA 15261.ORCID 0000-0002-3016-1951 Arthur S LevineDepartment of Neurobiology, University of Pittsburgh, 3501 Fifth Avenue Pittsburgh, Pennsylvania 15261.
Paul MunroSchool of Computing and Information, University of Pittsburgh, 135 North Bellefield Avenue Pittsburgh, PA 15260.
Jiang BianDepartment of Health Outcomes and Biomedical Informatics, University of Florida, 1889 Museum Road, 7th Floor, Suite 7000 Gainesville, FL 32611.ORCID 0000-0002-2238-5429 Jie XuDepartment of Health Outcomes and Biomedical Informatics, University of Florida, 1889 Museum Road, 7th Floor, Suite 7000 Gainesville, FL 32611.ORCID 0000-0001-5291-5198 Demetrius MaraganoreDepartment of Neurology, Tulane University School of Medicine, 1430 Tulane Avenue New Orleans, La 70112.ORCID 0000-0001-5351-3983 Karen SchliepDepartment of Family and Preventive Medicine, University of Utah Health, 375 Chipeta Way Ste. A Salt Lake City, Utah 84108.ORCID 0000-0003-1771-3157 Jonathan C SilversteinDepartment of Biomedical Informatics, University of Pittsburgh, 5607 Baum Blvd, Suite 500 Pittsburgh, PA 15206-3701.ORCID 0000-0002-9252-6039 Michelle KienholzClinical and Translational Science Institute, University of Pittsburgh, Meyran Ave Suite 7057, Pittsburgh, PA 15213.ORCID 0000-0001-9793-494X Helmet T KarimDepartment of Psychiatry, University of Pittsburgh, 3811 O'hara St., Pittsburgh, PA, 15213.ORCID 0000-0002-9286-0694 Funding
University of Pittsburgh Clinical and Translational Science InstituteUL1TR001857 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E · 2016 to 2025
$129.3MThe internship in Biomedical Research, Informatics, and Computer Science (iBRIC): Biomedical Informatics and Data Science research experiences for students from Minority Serving InstitutionsT15LM007059 · NLM · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI HARRY S HOCHHEISER · 1987 to 2026
$23.9MPopulation Neuroscience of Aging and Alzheimer's Disease (PNA)T32AG055381 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Caterina Rosano, Andrea L Rosso · 2018 to 2026
$2.7MUsing the literature to build causal models of retrospective observational dataR00LM013367 · NLM · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI MALEC, SCOTT ALEXANDER · 2023 to 2025
$746kPopulation neuroscience of sex differences in the Alzheimer's disease biomarker cascade: The role of cerebral small vessel diseaseK01AG071849 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI C. Elizabeth Shaaban · 2022 to 2026
$629kUsing the literature to build causal models of retrospective observational dataK99LM013367 · NLM · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI MALEC, SCOTT ALEXANDER · 2021 to 2022
$145kNCATS NIH HHS UL1 TR001857NIA NIH HHS K01 AG071849NIA NIH HHS T32 AG055381NLM NIH HHS K99 LM013367NLM NIH HHS R00 LM013367NLM NIH HHS T15 LM007059
6 · The paper itselfAbstract
introductionThere is need to detect and intervene in pre-clinical phases of Alzheimer's disease (AD). Electronic health records (EHRs) may help predict AD using machine learning methods.
methodsWe identified EHRs for 19,473 cases with AD and 111,922 controls. Records spanned 10 or more years prior to AD diagnosis. We trained a random forest model (employing 5-fold cross-validation with 2,499 features) to predict AD 10 years prior to its onset using a 75/25% train/test split and then computed permuted feature importance.
resultsWe achieved an area under the ROC curve of 0.80. Feature importance identified factors associated with AD, including age, sex, race, ethnicity, BMI, cardiovascular diseases, inflammation, pain, sleep and mood disorders, trauma, other neurodegenerative disorders, diuretics, colon-related disorders and procedures, seizures, and vitamin B12. DISCUSSION: This is the first EHR-based model to predict AD 10 years prior to onset, which could help predict AD and inform prevention/early intervention.
Indexed as
Alzheimer’s diseaseElectronic Health Recordmachine learningpredictionRandom Forest
Identifiers
PMID41292647
PMCPMC12642707
What OpenQuestion holds
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LicenceCC BY-ND
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