{"id":"https://openalex.org/W2586515896","doi":"https://doi.org/10.1145/3007195","title":"<i>Daehr</i>","display_name":"<i>Daehr</i>","publication_year":2017,"publication_date":"2017-02-08","ids":{"openalex":"https://openalex.org/W2586515896","doi":"https://doi.org/10.1145/3007195","mag":"2586515896"},"language":"en","primary_location":{"id":"doi:10.1145/3007195","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3007195","pdf_url":null,"source":{"id":"https://openalex.org/S2492086750","display_name":"ACM Transactions on Intelligent Systems and Technology","issn_l":"2157-6904","issn":["2157-6904","2157-6912"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Intelligent Systems and Technology","raw_type":"journal-article"},"type":"article","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/A5081254155","display_name":"Haoyi Xiong","orcid":"https://orcid.org/0000-0002-5451-3253"},"institutions":[{"id":"https://openalex.org/I20382870","display_name":"Missouri University of Science and Technology","ror":"https://ror.org/00scwqd12","country_code":"US","type":"education","lineage":["https://openalex.org/I20382870"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haoyi Xiong","raw_affiliation_strings":["Missouri University of Science and Technology, Missouri, USA"],"raw_orcid":"https://orcid.org/0000-0002-5451-3253","affiliations":[{"raw_affiliation_string":"Missouri University of Science and Technology, Missouri, USA","institution_ids":["https://openalex.org/I20382870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008048489","display_name":"Jinghe Zhang","orcid":"https://orcid.org/0000-0002-0537-2087"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jinghe Zhang","raw_affiliation_strings":["University of Virginia, VA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Virginia, VA, USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101775142","display_name":"Yu Huang","orcid":"https://orcid.org/0000-0002-5885-5365"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yu Huang","raw_affiliation_strings":["University of Virginia, VA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Virginia, VA, USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030030910","display_name":"Kevin Leach","orcid":"https://orcid.org/0000-0002-4001-3442"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kevin Leach","raw_affiliation_strings":["University of Virginia, VA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Virginia, VA, USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012728152","display_name":"Laura E. Barnes","orcid":"https://orcid.org/0000-0001-8224-5164"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Laura E. Barnes","raw_affiliation_strings":["University of Virginia, VA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Virginia, VA, USA","institution_ids":["https://openalex.org/I51556381"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3957,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.85660645,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"8","issue":"3","first_page":"1","last_page":"21"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13283","display_name":"Mental Health Research Topics","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9674999713897705,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7765038013458252},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.6225422620773315},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5716465711593628},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5194761157035828},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.5105010271072388},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.500483512878418},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.49817776679992676},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3880467414855957},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37320321798324585},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33847057819366455},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3312760889530182},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.23022881150245667},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10812079906463623}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7765038013458252},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.6225422620773315},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5716465711593628},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5194761157035828},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.5105010271072388},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.500483512878418},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.49817776679992676},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3880467414855957},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37320321798324585},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33847057819366455},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3312760889530182},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.23022881150245667},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10812079906463623},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3007195","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3007195","pdf_url":null,"source":{"id":"https://openalex.org/S2492086750","display_name":"ACM Transactions on Intelligent Systems and Technology","issn_l":"2157-6904","issn":["2157-6904","2157-6912"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Intelligent Systems and Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6800000071525574,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W257484075","https://openalex.org/W263382009","https://openalex.org/W379260703","https://openalex.org/W1484864026","https://openalex.org/W1512511032","https://openalex.org/W1513618424","https://openalex.org/W1525006452","https://openalex.org/W1799934227","https://openalex.org/W1956509155","https://openalex.org/W1965701254","https://openalex.org/W1973240358","https://openalex.org/W1976253807","https://openalex.org/W1983798833","https://openalex.org/W1984358873","https://openalex.org/W1985329916","https://openalex.org/W1988520084","https://openalex.org/W1998396834","https://openalex.org/W1999568948","https://openalex.org/W2001619934","https://openalex.org/W2004910511","https://openalex.org/W2005464046","https://openalex.org/W2014577670","https://openalex.org/W2023717039","https://openalex.org/W2027717478","https://openalex.org/W2032991527","https://openalex.org/W2033468335","https://openalex.org/W2056102627","https://openalex.org/W2058046352","https://openalex.org/W2065219958","https://openalex.org/W2083607783","https://openalex.org/W2091560152","https://openalex.org/W2093103229","https://openalex.org/W2100235169","https://openalex.org/W2103106495","https://openalex.org/W2103556204","https://openalex.org/W2106665921","https://openalex.org/W2107542203","https://openalex.org/W2113968881","https://openalex.org/W2114755499","https://openalex.org/W2116019577","https://openalex.org/W2119794178","https://openalex.org/W2122475441","https://openalex.org/W2123749188","https://openalex.org/W2124541940","https://openalex.org/W2125369647","https://openalex.org/W2129476886","https://openalex.org/W2156466771","https://openalex.org/W2160193995","https://openalex.org/W2172663006","https://openalex.org/W2197666063","https://openalex.org/W2216133675","https://openalex.org/W2259024711","https://openalex.org/W2395172628","https://openalex.org/W2401397987","https://openalex.org/W2433832342","https://openalex.org/W2465493330","https://openalex.org/W2490800645","https://openalex.org/W2914218031","https://openalex.org/W3104038823","https://openalex.org/W3141595720","https://openalex.org/W4294947750"],"related_works":["https://openalex.org/W2250488071","https://openalex.org/W2356150353","https://openalex.org/W2380744779","https://openalex.org/W1999647744","https://openalex.org/W2018643641","https://openalex.org/W1489099099","https://openalex.org/W2886934452","https://openalex.org/W2326614066","https://openalex.org/W2024369332","https://openalex.org/W1974955043"],"abstract_inverted_index":{"Electronic":[0],"health":[1,114,227],"records":[2],"(EHR)":[3],"provide":[4],"a":[5,13,98,157,197,248],"rich":[6],"source":[7],"of":[8,22,43,108,139,147,208],"temporal":[9],"data":[10,77,116,132,141],"that":[11],"present":[12],"unique":[14],"opportunity":[15],"to":[16,54,70,117,128,175,210],"characterize":[17],"disease":[18,34,62],"patterns":[19],"and":[20,95,142,215,247],"risk":[21,224],"imminent":[23],"disease.":[24,74],"While":[25],"many":[26],"data-mining":[27],"tools":[28],"have":[29,71],"been":[30],"adopted":[31],"for":[32,60,152,163,185,225],"EHR-based":[33],"early":[35,61],"detection,":[36],"linear":[37],"discriminant":[38],"analysis":[39],"(LDA)":[40],"is":[41,52],"one":[42],"the":[44,72,86,109,131,136,145,177,192,206,239],"most":[45],"commonly":[46],"used":[47,89],"statistical":[48],"methods.":[49],"However,":[50],"it":[51],"difficult":[53],"train":[55],"an":[56,106,172],"accurate":[57],"LDA":[58,91,110,123,153,209,214],"model":[59],"diagnosis":[63],"when":[64,155],"too":[65],"few":[66,158],"patients":[67],"are":[68,78,92,161],"known":[69],"target":[73],"Furthermore,":[75],"EHR":[76,140,160,200],"heterogeneous":[79],"with":[80,97,181],"significant":[81],"noise.":[82],"In":[83],"such":[84],"cases,":[85],"covariance":[87,178],"matrices":[88],"in":[90,218],"usually":[93],"singular":[94],"estimated":[96],"large":[99],"variance.":[100],"This":[101],"article":[102],"presents":[103],"Daehr":[104,127,189,236],",":[105],"extension":[107],"framework":[111],"using":[112,191],"electronic":[113],"record":[115],"address":[118],"these":[119,167],"issues.":[120],"Beyond":[121],"existing":[122],"analyzers,":[124],"we":[125,170],"propose":[126],"(1)":[129],"eliminate":[130],"noise":[133],"caused":[134],"by":[135,242],"manual":[137],"encoding":[138],"(2)":[143],"lower":[144],"variance":[146],"parameter":[148],"(covariance":[149],"matrices)":[150],"estimation":[151,180],"models":[154],"only":[156],"patients\u2019":[159],"available":[162],"training.":[164],"To":[165],"achieve":[166],"two":[168],"goals,":[169],"designed":[171],"iterative":[173],"algorithm":[174],"improve":[176],"matrix":[179],"embedded":[182],"data-noise/parameter-variance":[183],"reduction":[184],"LDA.":[186],"We":[187],"evaluated":[188],"extensively":[190],"College":[193],"Health":[194],"Surveillance":[195],"Network,":[196],"large,":[198],"real-world":[199],"dataset.":[201],"Specifically,":[202],"our":[203],"experiments":[204],"compared":[205],"performance":[207],"three":[211,240],"baselines":[212,241],"(i.e.,":[213],"its":[216],"derivatives)":[217],"identifying":[219],"college":[220],"students":[221],"at":[222],"high":[223],"mental":[226],"disorders":[228],"from":[229],"23":[230],"U.S.":[231],"universities.":[232],"Experimental":[233],"results":[234],"demonstrate":[235],"significantly":[237],"outperforms":[238],"achieving":[243],"1.4%--19.4%":[244],"higher":[245,250],"accuracy":[246],"7.5%--43.5%":[249],"F1-score.":[251]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2017-02-17T00:00:00"}