{"id":"https://openalex.org/W4414648348","doi":"https://doi.org/10.1109/cibcb66090.2025.11177117","title":"Alzheimer's Disease Risk Prediction in the Elderly: A Machine Learning Approach Combining Clinical Characteristics and Polygenic Risk Scores","display_name":"Alzheimer's Disease Risk Prediction in the Elderly: A Machine Learning Approach Combining Clinical Characteristics and Polygenic Risk Scores","publication_year":2025,"publication_date":"2025-08-20","ids":{"openalex":"https://openalex.org/W4414648348","doi":"https://doi.org/10.1109/cibcb66090.2025.11177117"},"language":"en","primary_location":{"id":"doi:10.1109/cibcb66090.2025.11177117","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cibcb66090.2025.11177117","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013309172","display_name":"Justin Bo\u2010Kai Hsu","orcid":null},"institutions":[{"id":"https://openalex.org/I99908691","display_name":"Yuan Ze University","ror":"https://ror.org/01fv1ds98","country_code":"TW","type":"education","lineage":["https://openalex.org/I99908691"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Justin Bo-Kai Hsu","raw_affiliation_strings":["Yuan Ze University,College of Informatics,Department of Computer Science and Engineering,Taoyuan City,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yuan Ze University,College of Informatics,Department of Computer Science and Engineering,Taoyuan City,Taiwan","institution_ids":["https://openalex.org/I99908691"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030737061","display_name":"Cheng\u2010Yang Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I47519274","display_name":"Taipei Medical University","ror":"https://ror.org/05031qk94","country_code":"TW","type":"education","lineage":["https://openalex.org/I47519274"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Cheng-Yang Lee","raw_affiliation_strings":["Taipei Medical University,Graduate Institute of Biomedical Informatics, College of Medical Science and Technology,New Taipei City,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Taipei Medical University,Graduate Institute of Biomedical Informatics, College of Medical Science and Technology,New Taipei City,Taiwan","institution_ids":["https://openalex.org/I47519274"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111918234","display_name":"Jia\u2010Ruey Tsai","orcid":null},"institutions":[{"id":"https://openalex.org/I2802331550","display_name":"Taipei Medical University Hospital","ror":"https://ror.org/03k0md330","country_code":"TW","type":"healthcare","lineage":["https://openalex.org/I2802331550"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jia-Ruey Tsai","raw_affiliation_strings":["Taipei Medical University Hospital,Department of Hematology & Oncology,Taipei City,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Taipei Medical University Hospital,Department of Hematology & Oncology,Taipei City,Taiwan","institution_ids":["https://openalex.org/I2802331550"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076657463","display_name":"Vijesh Kumar Yadav","orcid":"https://orcid.org/0000-0002-2679-1205"},"institutions":[{"id":"https://openalex.org/I47519274","display_name":"Taipei Medical University","ror":"https://ror.org/05031qk94","country_code":"TW","type":"education","lineage":["https://openalex.org/I47519274"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Vijesh Kumar Yadav","raw_affiliation_strings":["Taipei Medical University,Division of Gastroenterology and Hepatology,Department of Internal Medicine, School of Medicine, College of Medicine,Taipei City,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Taipei Medical University,Division of Gastroenterology and Hepatology,Department of Internal Medicine, School of Medicine, College of Medicine,Taipei City,Taiwan","institution_ids":["https://openalex.org/I47519274"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074412599","display_name":"Chuan Huang","orcid":"https://orcid.org/0000-0001-6052-0663"},"institutions":[{"id":"https://openalex.org/I47519274","display_name":"Taipei Medical University","ror":"https://ror.org/05031qk94","country_code":"TW","type":"education","lineage":["https://openalex.org/I47519274"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chuan Huang","raw_affiliation_strings":["Taipei Medical University,Graduate Institute of Biomedical Informatics, College of Medical Science and Technology,New Taipei City,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Taipei Medical University,Graduate Institute of Biomedical Informatics, College of Medical Science and Technology,New Taipei City,Taiwan","institution_ids":["https://openalex.org/I47519274"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109392757","display_name":"Tzu-Hao Chang","orcid":null},"institutions":[{"id":"https://openalex.org/I47519274","display_name":"Taipei Medical University","ror":"https://ror.org/05031qk94","country_code":"TW","type":"education","lineage":["https://openalex.org/I47519274"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Tzu-Hao Chang","raw_affiliation_strings":["Taipei Medical University,Graduate Institute of Biomedical Informatics, College of Medical Science and Technology,New Taipei City,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Taipei Medical University,Graduate Institute of Biomedical Informatics, College of Medical Science and Technology,New Taipei City,Taiwan","institution_ids":["https://openalex.org/I47519274"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.35201,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.8759999871253967,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.8759999871253967,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/biobank","display_name":"Biobank","score":0.6133000254631042},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.5666999816894531},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5461000204086304},{"id":"https://openalex.org/keywords/framingham-risk-score","display_name":"Framingham Risk Score","score":0.5192000269889832},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.5026999711990356},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.439300000667572},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4341000020503998},{"id":"https://openalex.org/keywords/polygenic-risk-score","display_name":"Polygenic risk score","score":0.38999998569488525},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.3894999921321869}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7159000039100647},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6751000285148621},{"id":"https://openalex.org/C116567970","wikidata":"https://www.wikidata.org/wiki/Q864217","display_name":"Biobank","level":2,"score":0.6133000254631042},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.5666999816894531},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5461000204086304},{"id":"https://openalex.org/C11783203","wikidata":"https://www.wikidata.org/wiki/Q5478027","display_name":"Framingham Risk Score","level":3,"score":0.5192000269889832},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.5026999711990356},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.439300000667572},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4341000020503998},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3986000120639801},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3978999853134155},{"id":"https://openalex.org/C2993137441","wikidata":"https://www.wikidata.org/wiki/Q28135712","display_name":"Polygenic risk score","level":5,"score":0.38999998569488525},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.3894999921321869},{"id":"https://openalex.org/C12174686","wikidata":"https://www.wikidata.org/wiki/Q1058438","display_name":"Risk assessment","level":2,"score":0.3813000023365021},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.36010000109672546},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.320499986410141},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.31040000915527344},{"id":"https://openalex.org/C153209595","wikidata":"https://www.wikidata.org/wiki/Q501128","display_name":"Single-nucleotide polymorphism","level":4,"score":0.30660000443458557},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C186413461","wikidata":"https://www.wikidata.org/wiki/Q744727","display_name":"Genetic association","level":5,"score":0.2944999933242798},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.29409998655319214},{"id":"https://openalex.org/C17923572","wikidata":"https://www.wikidata.org/wiki/Q7250160","display_name":"Propensity score matching","level":2,"score":0.27709999680519104},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.2766000032424927},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.2732999920845032},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C160798450","wikidata":"https://www.wikidata.org/wiki/Q4230870","display_name":"Concordance","level":2,"score":0.2621000111103058},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.26019999384880066}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cibcb66090.2025.11177117","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cibcb66090.2025.11177117","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320331164","display_name":"National Science and Technology Council","ror":"https://ror.org/00wnb9798"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2060427373","https://openalex.org/W2161633633","https://openalex.org/W2169147852","https://openalex.org/W2193207784","https://openalex.org/W2295598076","https://openalex.org/W2723723801","https://openalex.org/W2803332630","https://openalex.org/W2886752110","https://openalex.org/W2901303766","https://openalex.org/W3096808785","https://openalex.org/W4206046172","https://openalex.org/W4243334883","https://openalex.org/W4297025669","https://openalex.org/W4308616307","https://openalex.org/W4311666194","https://openalex.org/W4313830798","https://openalex.org/W4362666447","https://openalex.org/W4380422060","https://openalex.org/W4386945606"],"related_works":[],"abstract_inverted_index":{"Motivation:":[0],"Alzheimer's":[1],"disease":[2],"(AD)":[3],"is":[4,22,347],"the":[5,12,45,73,88,149,186,190,194,212,216,221,285,311,325,351],"most":[6],"common":[7],"type":[8],"of":[9,14,19,47,76,151,200,227,281,313,327,342,354],"dementia.":[10],"Given":[11],"lack":[13],"a":[15],"cure,":[16],"early":[17],"identification":[18],"high-risk":[20],"populations":[21,336],"crucial":[23],"for":[24,66,80,107,141,180,318],"timely":[25],"prevention.":[26],"While":[27],"several":[28],"studies":[29,116],"have":[30],"focused":[31],"on":[32,118,203,230,240],"AD":[33,77,103,314],"risk":[34,50,78,104,137,188,214,290,315,345],"prediction,":[35,189,215],"single":[36],"feature":[37],"(e.g.,":[38],"age)":[39],"may":[40],"dominate":[41],"model":[42,192,218,268,287],"performance,":[43,196,223],"limiting":[44],"discovery":[46],"other":[48,343],"potential":[49,344],"factors.":[51],"This":[52,83,299],"study":[53,84,300],"incorporates":[54],"key":[55,247],"features":[56,153,206,305],"identified":[57],"in":[58],"previous":[59],"research":[60,330],"and":[61,68,94,97,100,146,148,161,176,182,207,237,262,272,279,295,337],"applies":[62],"propensity":[63],"score":[64,138],"matching":[65,264],"age":[67],"sex,":[69],"aiming":[70],"to":[71,91,123,154,322,349],"improve":[72],"predictive":[74],"performance":[75,183],"models":[79,106,251,317],"older":[81,108,319],"adults.Methods:":[82],"utilized":[85],"data":[86,96],"from":[87],"UK":[89],"Biobank":[90],"integrate":[92],"genetic":[93],"clinical":[95,205,232,271,304,352],"developed":[98],"5-year":[99,187,267],"10-":[101],"year":[102],"prediction":[105,156,181,316],"adults,":[109],"respectively.":[110],"The":[111,266],"workflow":[112],"included":[113,252],"genome-wide":[114],"association":[115],"(GWAS)":[117],"433,589":[119],"participants":[120,143],"were":[121,164],"conducted":[122],"identify":[124],"significant":[125,162,209,235],"Single":[126],"nucleotide":[127],"polymorphisms":[128],"(SNPs)":[129],"under":[130],"three":[131],"p-value":[132],"thresholds,":[133],"followed":[134],"by":[135],"polygenic":[136],"(PRS)":[139],"calculation":[140],"13,282":[142],"using":[144],"PRSice-2":[145],"Lassosum,":[147],"integration":[150],"multiple":[152],"construct":[155],"models.":[157,356],"Clinical":[158],"features,":[159,233],"PRS,":[160,328],"SNPs":[163],"then":[165],"incorporated":[166],"into":[167],"four":[168],"machine":[169],"learning":[170],"models:":[171],"Logistic":[172],"Regression,":[173],"LightGBM,":[174],"XGBoost,":[175],"Multi-Layer":[177],"Perceptron":[178],"(MLP)":[179],"comparison.Results:":[184],"For":[185,211],"MLP":[191,217],"demonstrated":[193,220],"best":[195,222],"achieving":[197,224],"an":[198,225],"AUC":[199,226],"0.88":[201],"based":[202,229,239],"37":[204,231],"206":[208,234],"SNPs.":[210,242],"10-year":[213,286],"also":[219],"0.89":[228],"SNPs,":[236],"PRS":[238,307],"these":[241,355],"SHAP":[243],"analysis":[244],"revealed":[245],"that":[246,302],"contributors":[248],"across":[249,334],"both":[250],"ApoE":[253],"genotype,":[254],"urinary":[255],"tract":[256],"infection":[257],"(N390),":[258],"disorientation,":[259],"depressive":[260],"symptoms,":[261],"pairs":[263],"time.":[265],"emphasized":[269],"immediate":[270],"cognitive":[273],"indicators":[274],"such":[275],"as":[276],"reaction":[277],"time":[278],"number":[280],"medications":[282],"taken,":[283],"whereas":[284],"highlighted":[288],"long-term":[289],"factors":[291,346],"including":[292],"BMI,":[293],"diabetes,":[294],"peak":[296],"expiratory":[297],"flow.Conclusion:":[298],"demonstrates":[301],"integrating":[303],"with":[306],"can":[308],"effectively":[309],"enhance":[310,350],"accuracy":[312],"adults.":[320],"However,":[321],"further":[323,340],"validate":[324],"utility":[326],"future":[329],"should":[331],"involve":[332],"collaborations":[333],"diverse":[335],"databases.":[338],"Additionally,":[339],"exploration":[341],"needed":[348],"applicability":[353]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}