{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T17:23:03Z","timestamp":1777051383126,"version":"3.51.4"},"reference-count":53,"publisher":"Public Library of Science (PLoS)","issue":"10","license":[{"start":{"date-parts":[[2023,10,19]],"date-time":"2023-10-19T00:00:00Z","timestamp":1697673600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100007333","name":"Alzheimer's Disease Neuroimaging Initiative","doi-asserted-by":"crossref","award":["National Institutes of Health Grant U01 AG024904"],"award-info":[{"award-number":["National Institutes of Health Grant U01 AG024904"]}],"id":[{"id":"10.13039\/100007333","id-type":"DOI","asserted-by":"crossref"}]},{"name":"DOD ADNI","award":["Department of Defense award number W81XWH-12-2-0012"],"award-info":[{"award-number":["Department of Defense award number W81XWH-12-2-0012"]}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000070","name":"National Institute of Biomedical Imaging and Bioengineering","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000070","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006483","name":"AbbVie","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006483","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000957","name":"Alzheimer's Association","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000957","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100002565","name":"Alzheimer's Drug Discovery Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100002565","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Araclon Biotech"},{"DOI":"10.13039\/100007742","name":"BioClinica, Inc.","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100007742","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100005614","name":"Biogen","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100005614","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Bristol-Myers Squibb Company"},{"name":"CereSpir, Inc."},{"name":"Cogstate"},{"name":"Eisai Inc."},{"name":"Elan Pharmaceuticals, Inc."},{"DOI":"10.13039\/100004312","name":"Eli Lilly and Company","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100004312","id-type":"DOI","asserted-by":"publisher"}]},{"name":"EuroImmun"},{"name":"F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc."},{"name":"Fujirebio"},{"DOI":"10.13039\/100006775","name":"GE Healthcare","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006775","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100015725","name":"IXICO Ltd.","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100015725","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Janssen Alzheimer Immunotherapy Research & Development, LLC."},{"name":"Johnson & Johnson Pharmaceutical Research & Development LLC."},{"name":"Lumosity"},{"DOI":"10.13039\/501100013327","name":"Lundbeck","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100013327","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100004334","name":"Merck & Co., Inc.","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100004334","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Meso Scale Diagnostics, LLC."},{"name":"NeuroRx Research"},{"name":"Neurotrack Technologies"},{"DOI":"10.13039\/100008272","name":"Novartis Pharmaceuticals Corporation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100008272","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100004319","name":"Pfizer Inc.","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100004319","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Piramal Imaging"},{"DOI":"10.13039\/501100011725","name":"Servier","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100011725","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100008373","name":"Takeda Pharmaceutical Company","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100008373","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Transition Therapeutics"},{"DOI":"10.13039\/501100000024","name":"Canadian Institutes of Health Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000024","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000009","name":"Foundation for the National Institutes of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000009","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100009804","name":"Northern California Institute for Research and Education","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100009804","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Alzheimer's Therapeutic Research Institute at the University of Southern California"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:sec id=\"sec001\">\n<jats:title>Introduction<\/jats:title>\n<jats:p>The Amyloid\/Tau\/Neurodegeneration (ATN) framework was proposed to identify the preclinical biological state of Alzheimer\u2019s disease (AD). We investigated whether ATN phenotype can be predicted using routinely collected research cohort data.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec002\">\n<jats:title>Methods<\/jats:title>\n<jats:p>927 EPAD LCS cohort participants free of dementia or Mild Cognitive Impairment were separated into 5 ATN categories. We used machine learning (ML) methods to identify a set of significant features separating each neurodegeneration-related group from controls (A-T-(N)-). Random Forest and linear-kernel SVM with stratified 5-fold cross validations were used to optimize model whose performance was then tested in the ADNI database.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec003\">\n<jats:title>Results<\/jats:title>\n<jats:p>Our optimal results outperformed ATN cross-validated logistic regression models by between 2.2% and 8.3%. The optimal feature sets were not consistent across the 4 models with the AD pathologic change vs controls set differing the most from the rest. Because of that we have identified a subset of 10 features that yield results very close or identical to the optimal.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec004\">\n<jats:title>Discussion<\/jats:title>\n<jats:p>Our study demonstrates the gains offered by ML in generating ATN risk prediction over logistic regression models among pre-dementia individuals.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0288039","type":"journal-article","created":{"date-parts":[[2023,10,19]],"date-time":"2023-10-19T17:50:22Z","timestamp":1697737822000},"page":"e0288039","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":5,"title":["Identification of preclinical dementia according to ATN classification for stratified trial recruitment: A machine learning approach"],"prefix":"10.1371","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6813-8493","authenticated-orcid":true,"given":"Ivan","family":"Koychev","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Evgeniy","family":"Marinov","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Simon","family":"Young","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sophia","family":"Lazarova","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Denitsa","family":"Grigorova","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dean","family":"Palejev","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"340","published-online":{"date-parts":[[2023,10,19]]},"reference":[{"key":"pone.0288039.ref001","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1016\/j.jalz.2018.02.018","article-title":"NIA\u2010AA Research Framework: Toward a biological definition of Alzheimer\u2019s disease.","volume":"14","author":"CR Jack","year":"2018","journal-title":"Alzheimers Dement"},{"key":"pone.0288039.ref002","doi-asserted-by":"crossref","DOI":"10.1126\/scitranslmed.3002609","article-title":"Testing the Right Target and Right Drug at the Right Stage.","volume":"3","author":"RA Sperling","year":"2011","journal-title":"Sci Transl Med"},{"key":"pone.0288039.ref003","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":"G Livingston","year":"2020","journal-title":"The Lancet"},{"key":"pone.0288039.ref004","doi-asserted-by":"crossref","first-page":"735","DOI":"10.1016\/S1474-4422(06)70537-3","article-title":"Risk score for the prediction of dementia risk in 20 years among middle aged people: a longitudinal, population-based study","volume":"5","author":"M Kivipelto","year":"2006","journal-title":"Lancet Neurol"},{"key":"pone.0288039.ref005","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1186\/s13195-022-01067-8","article-title":"Predicting conversion of brain \u03b2-amyloid positivity in amyloid-negative individuals","volume":"14","author":"CJ Park","year":"2022","journal-title":"Alzheimers Res Ther"},{"key":"pone.0288039.ref006","doi-asserted-by":"crossref","first-page":"e2425","DOI":"10.1212\/WNL.0000000000200553","article-title":"Predicting Amyloid Positivity in Cognitively Unimpaired Older Adults: A Machine Learning Approach Using A4 Data.","volume":"98","author":"KK Petersen","year":"2022","journal-title":"Neurology"},{"key":"pone.0288039.ref007","doi-asserted-by":"crossref","first-page":"585","DOI":"10.1038\/s41398-021-01709-9","article-title":"Plasma phosphorylated-tau181 as a predictive biomarker for Alzheimer\u2019s amyloid, tau and FDG PET status.","volume":"11","author":"X-N Shen","year":"2021","journal-title":"Transl Psychiatry"},{"key":"pone.0288039.ref008","doi-asserted-by":"crossref","first-page":"e1580","DOI":"10.1212\/WNL.0000000000009240","article-title":"Total A\u03b2 42 \/A\u03b2 40 ratio in plasma predicts amyloid-PET status, independent of clinical AD diagnosis","volume":"94","author":"JD Doecke","year":"2020","journal-title":"Neurology"},{"key":"pone.0288039.ref009","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1186\/s13195-020-00711-5","article-title":"Prediction of Alzheimer\u2019s disease biomarker status defined by the \u2018ATN framework\u2019 among cognitively healthy individuals: results from the EPAD longitudinal cohort study.","volume":"12","author":"The European Prevention of Alzheimer\u2019s Dementia (EPAD) Consortium","year":"2020","journal-title":"Alzheimers Res Ther"},{"key":"pone.0288039.ref010","doi-asserted-by":"crossref","first-page":"2326","DOI":"10.1093\/eurheartj\/ehr133","article-title":"Predictive utility of the Framingham general cardiovascular disease risk profile for cognitive function: evidence from the Whitehall II study","volume":"32","author":"S Kaffashian","year":"2011","journal-title":"Eur Heart J"},{"key":"pone.0288039.ref011","doi-asserted-by":"crossref","first-page":"404","DOI":"10.1161\/01.STR.0000103141.82869.77","article-title":"Framingham Stroke Risk Profile and Lowered Cognitive Performance","volume":"35","author":"MF Elias","year":"2004","journal-title":"Stroke"},{"key":"pone.0288039.ref012","doi-asserted-by":"crossref","first-page":"e021017","DOI":"10.1136\/bmjopen-2017-021017","article-title":"European Prevention of Alzheimer\u2019s Dementia Longitudinal Cohort Study (EPAD LCS): study protocol.","volume":"8","author":"A Solomon","year":"2018","journal-title":"BMJ Open"},{"key":"pone.0288039.ref013","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1212\/WNL.0b013e3181cb3e25","article-title":"Alzheimer\u2019s Disease Neuroimaging Initiative (ADNI): Clinical characterization.","volume":"74","author":"RC Petersen","year":"2010","journal-title":"Neurology"},{"key":"pone.0288039.ref014","doi-asserted-by":"crossref","first-page":"177","DOI":"10.3233\/JAD-200900","article-title":"Blood-Based ATN Biomarkers of Alzheimer\u2019s Disease: A Meta-Analysis","volume":"79","author":"I Koychev","year":"2021","journal-title":"J Alzheimers Dis"},{"key":"pone.0288039.ref015","first-page":"1","article-title":"THE EUROPEAN PREVENTION OF ALZHEIMER\u2019S DEMENTIA (EPAD) LONGITUDINAL COHORT STUDY: BASELINE DATA RELEASE V500.0.","author":"CW Ritchie","year":"2019","journal-title":"J Prev Alzheimers Dis"},{"key":"pone.0288039.ref016","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/0022-3956(75)90026-6","article-title":"Mini-mental state","volume":"12","author":"MF Folstein","year":"1975","journal-title":"J Psychiatr Res"},{"key":"pone.0288039.ref017","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1159\/000477718","article-title":"Visual Ratings of Medial Temporal Lobe Atrophy Correlate with CSF Tau Indices in Clinical Variants of Early-Onset Alzheimer Disease.","volume":"44","author":"E Granadillo","year":"2017","journal-title":"Dement Geriatr Cogn Disord"},{"key":"pone.0288039.ref018","author":"Roche Diagnostics International Ltd","year":"2017","journal-title":"Elecsys\u00ae Phospho-Tau (181P) CSF"},{"key":"pone.0288039.ref019","author":"Roche Diagnostics International Ltd","year":"2018","journal-title":"Elecsys\u00ae \u03b2-Amyloid (1\u201342) CSF"},{"key":"pone.0288039.ref020","author":"Roche Diagnostics International Ltd","year":"2017","journal-title":"Elecsys\u00ae Total-Tau CSF"},{"key":"pone.0288039.ref021","doi-asserted-by":"crossref","first-page":"967","DOI":"10.1136\/jnnp.55.10.967","article-title":"Atrophy of medial temporal lobes on MRI in \u201cprobable\u201d Alzheimer\u2019s disease and normal ageing: diagnostic value and neuropsychological correlates.","volume":"55","author":"P Scheltens","year":"1992","journal-title":"J Neurol Neurosurg Psychiatry"},{"key":"pone.0288039.ref022","doi-asserted-by":"crossref","first-page":"3147","DOI":"10.1007\/s00330-016-4726-3","article-title":"Practical use of visual medial temporal lobe atrophy cut-off scores in Alzheimer\u2019s disease: Validation in a large memory clinic population.","volume":"27","author":"JJ Claus","year":"2017","journal-title":"Eur Radiol"},{"key":"pone.0288039.ref023","doi-asserted-by":"crossref","first-page":"989","DOI":"10.1016\/j.jalz.2018.02.013","article-title":"Plasma phospho\u2010tau181 increases with Alzheimer\u2019s disease clinical severity and is associated with tau\u2010 and amyloid\u2010positron emission tomography.","volume":"14","author":"MM Mielke","year":"2018","journal-title":"Alzheimers Dement"},{"key":"pone.0288039.ref024","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1093\/brain\/awaa399","article-title":"Time course of phosphorylated-tau181 in blood across the Alzheimer\u2019s disease spectrum","volume":"144","author":"A Moscoso","year":"2021","journal-title":"Brain"},{"key":"pone.0288039.ref025","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1186\/s13195-021-00802-x","article-title":"Plasma pTau181 predicts cortical brain atrophy in aging and Alzheimer\u2019s disease","volume":"13","author":"L. Tissot C","year":"2021","journal-title":"Alzheimers Res Ther"},{"key":"pone.0288039.ref026","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1038\/s41591-020-0762-2","article-title":"Diagnostic value of plasma phosphorylated tau181 in Alzheimer\u2019s disease and frontotemporal lobar degeneration","volume":"26","author":"EH Thijssen","year":"2020","journal-title":"Nat Med"},{"key":"pone.0288039.ref027","doi-asserted-by":"crossref","first-page":"695696","DOI":"10.3389\/fneur.2021.695696","article-title":"Plasma p-tau181 Level Predicts Neurodegeneration and Progression to Alzheimer\u2019s Dementia: A Longitudinal Study.","volume":"12","author":"Y-L Wang","year":"2021","journal-title":"Front Neurol"},{"key":"pone.0288039.ref028","article-title":"Expanding the Use of Weight of Evidence and Information Value to Continuous Dependent Variables for Variable Reduction and Scorecard Development.","author":"Lin Alec Zhixiao","year":"2014","journal-title":"Paper SD-84"},{"key":"pone.0288039.ref029","doi-asserted-by":"crossref","first-page":"1545","DOI":"10.1111\/j.1539-6924.2005.00699.x","article-title":"Weight of Evidence: A Review of Concept and Methods: Weight of Evidence.","volume":"25","author":"DL Weed","year":"2005","journal-title":"Risk Anal"},{"key":"pone.0288039.ref030","author":"Klaudia Nazarko","year":"2020","journal-title":"Churn analysis using IV and WOE in Python"},{"key":"pone.0288039.ref031","first-page":"785","volume-title":"Proc. 22nd ACM SIGKDD Int. Conf. Knowl. Discov","author":"T Chen","year":"2016"},{"key":"pone.0288039.ref032","article-title":"Gradient Boosting Machine: A Survey.","author":"Z He","year":"2019","journal-title":"ArXiv190806951 Cs Stat"},{"key":"pone.0288039.ref033","first-page":"2825","article-title":"Scikit-learn: Machine Learning in Python.","volume":"12","author":"F Pedregosa","year":"2011","journal-title":"J Mach Learn Res"},{"key":"pone.0288039.ref034","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"L. Breiman","year":"2001","journal-title":"Mach Learn"},{"key":"pone.0288039.ref035","article-title":"Random Forests: some methodological insights.","author":"R Genuer","year":"2008","journal-title":"ArXiv08113619 Stat"},{"key":"pone.0288039.ref036","unstructured":"Hastie T, Tibshirani R, Friedman J. The Elements of Statistical Learning. 2nd ed. New York, NY: Springer; n.d."},{"key":"pone.0288039.ref037","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/s10994-006-6226-1","article-title":"Extremely randomized trees","volume":"63","author":"P Geurts","year":"2006","journal-title":"Mach Learn"},{"key":"pone.0288039.ref038","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1007\/BF00058655","article-title":"Bagging predictors","volume":"24","author":"L. Breiman","year":"1996","journal-title":"Mach Learn"},{"key":"pone.0288039.ref039","article-title":"The return of AdaBoost.MH: multi-class Hamming trees.","author":"B. K\u00e9gl","year":"2013","journal-title":"ArXiv13126086 Cs"},{"key":"pone.0288039.ref040","first-page":"1137","volume-title":"Proc. 14th Int. Jt. Conf. Artif. Intell","author":"R. Kohavi","year":"1995"},{"key":"pone.0288039.ref041","doi-asserted-by":"crossref","first-page":"1389","DOI":"10.1109\/LSP.2014.2337313","article-title":"Fast Implementation of DeLong\u2019s Algorithm for Comparing the Areas Under Correlated Receiver Operating Characteristic Curves","volume":"21","author":"X Sun","year":"2014","journal-title":"IEEE Signal Process Lett"},{"key":"pone.0288039.ref042","doi-asserted-by":"crossref","first-page":"861","DOI":"10.1016\/j.patrec.2005.10.010","article-title":"An introduction to ROC analysis","volume":"27","author":"T. Fawcett","year":"2006","journal-title":"Pattern Recognit Lett"},{"key":"pone.0288039.ref043","doi-asserted-by":"crossref","DOI":"10.1002\/9781118548387","volume-title":"Applied Logistic Regression","author":"DW Hosmer","year":"2013","edition":"1"},{"key":"pone.0288039.ref044","doi-asserted-by":"crossref","first-page":"539","DOI":"10.1212\/WNL.0000000000002923","article-title":"A\/T\/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers","volume":"87","author":"CR Jack","year":"2016","journal-title":"Neurology"},{"key":"pone.0288039.ref045","doi-asserted-by":"crossref","first-page":"fcad015","DOI":"10.1093\/braincomms\/fcad015","article-title":"Plasma amyloid-\u03b242\/40 and apolipoprotein E for amyloid PET pre-screening in secondary prevention trials of Alzheimer\u2019s disease","volume":"5","author":"NC Cullen","year":"2023","journal-title":"Brain Commun"},{"key":"pone.0288039.ref046","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1038\/nrneurol.2015.251","article-title":"Suspected non-Alzheimer disease pathophysiology\u2014concept and controversy.","volume":"12","author":"CR Jack","year":"2016","journal-title":"Nat Rev Neurol"},{"key":"pone.0288039.ref047","doi-asserted-by":"crossref","DOI":"10.15252\/emmm.202012921","article-title":"Novel tau biomarkers phosphorylated at T181, T217 or T231 rise in the initial stages of the preclinical Alzheimer\u2019s continuum when only subtle changes in A\u03b2 pathology are detected","volume":"12","author":"M Su\u00e1rez\u2010Calvet","year":"2020","journal-title":"EMBO Mol Med"},{"key":"pone.0288039.ref048","author":"G James","year":"2021","edition":"2"},{"key":"pone.0288039.ref049","doi-asserted-by":"crossref","first-page":"e040766","DOI":"10.1136\/bmjopen-2020-040766","article-title":"Dementias Platform UK Clinical Studies and Great Minds Register: protocol of a targeted brain health studies recontact database","volume":"10","author":"I Koychev","year":"2020","journal-title":"BMJ Open"},{"key":"pone.0288039.ref050","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1136\/eb-2018-102890","article-title":"Digital technologies for the assessment of cognition: a clinical review.","volume":"21","author":"A Chinner","year":"2018","journal-title":"Evid Based Ment Health"},{"key":"pone.0288039.ref051","doi-asserted-by":"crossref","first-page":"954","DOI":"10.1038\/s41591-021-01382-x","article-title":"Biomarkers for neurodegenerative diseases","volume":"27","author":"O. Hansson","year":"2021","journal-title":"Nat Med"},{"key":"pone.0288039.ref052","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1080\/13803395.2020.1714551","article-title":"Gallery Game: Smartphone-based assessment of long-term memory in adults at risk of Alzheimer\u2019s disease.","volume":"42","author":"C Lancaster","year":"2020","journal-title":"J Clin Exp Neuropsychol"},{"key":"pone.0288039.ref053","doi-asserted-by":"crossref","first-page":"1803","DOI":"10.1016\/j.procs.2017.05.149","article-title":"Parallel Monte Carlo on Intel MIC Architecture.","volume":"108","author":"E Atanassov","year":"2017","journal-title":"Procedia Comput Sci"}],"container-title":["PLOS ONE"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0288039","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,19]],"date-time":"2023-10-19T17:51:43Z","timestamp":1697737903000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0288039"}},"subtitle":[],"editor":[{"given":"Stephen D.","family":"Ginsberg","sequence":"first","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2023,10,19]]},"references-count":53,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2023,10,19]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pone.0288039","relation":{},"ISSN":["1932-6203"],"issn-type":[{"value":"1932-6203","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10,19]]}}}