{"id":"https://openalex.org/W2048651988","doi":"https://doi.org/10.1145/2808719.2808741","title":"Bone disease prediction and phenotype discovery using feature representation over electronic health records","display_name":"Bone disease prediction and phenotype discovery using feature representation over electronic health records","publication_year":2015,"publication_date":"2015-09-09","ids":{"openalex":"https://openalex.org/W2048651988","doi":"https://doi.org/10.1145/2808719.2808741","mag":"2048651988"},"language":"en","primary_location":{"id":"doi:10.1145/2808719.2808741","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2808719.2808741","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics","raw_type":"proceedings-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/A5100627144","display_name":"Hui Li","orcid":"https://orcid.org/0000-0002-8866-5941"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hui Li","raw_affiliation_strings":["State University of New York at Buffalo"],"affiliations":[{"raw_affiliation_string":"State University of New York at Buffalo","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100713499","display_name":"LI Xiao-yi","orcid":"https://orcid.org/0000-0002-5560-3795"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaoyi Li","raw_affiliation_strings":["State University of New York at Buffalo"],"affiliations":[{"raw_affiliation_string":"State University of New York at Buffalo","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001445783","display_name":"Xiaowei Jia","orcid":"https://orcid.org/0000-0001-8544-5233"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaowei Jia","raw_affiliation_strings":["State University of New York at Buffalo"],"affiliations":[{"raw_affiliation_string":"State University of New York at Buffalo","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002609733","display_name":"Murali Ramanathan","orcid":"https://orcid.org/0000-0002-9943-150X"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Murali Ramanathan","raw_affiliation_strings":["State University of New York at Buffalo"],"affiliations":[{"raw_affiliation_string":"State University of New York at Buffalo","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013588572","display_name":"Aidong Zhang","orcid":"https://orcid.org/0000-0001-9723-3246"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aidong Zhang","raw_affiliation_strings":["State University of New York at Buffalo"],"affiliations":[{"raw_affiliation_string":"State University of New York at Buffalo","institution_ids":["https://openalex.org/I63190737"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100627144"],"corresponding_institution_ids":["https://openalex.org/I63190737"],"apc_list":null,"apc_paid":null,"fwci":0.4314,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.76023645,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"7","issue":null,"first_page":"212","last_page":"221"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9929999709129333,"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/T10862","display_name":"AI in cancer detection","score":0.9929999709129333,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9918000102043152,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.989300012588501,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6323659420013428},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6170491576194763},{"id":"https://openalex.org/keywords/health-records","display_name":"Health records","score":0.5502576231956482},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5493072867393494},{"id":"https://openalex.org/keywords/clinical-phenotype","display_name":"Clinical phenotype","score":0.4299767017364502},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4206872284412384},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3947394788265228},{"id":"https://openalex.org/keywords/phenotype","display_name":"Phenotype","score":0.36166149377822876},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33664003014564514},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.11074379086494446},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.08593970537185669},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.06729260087013245}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6323659420013428},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6170491576194763},{"id":"https://openalex.org/C3019952477","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Health records","level":3,"score":0.5502576231956482},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5493072867393494},{"id":"https://openalex.org/C3020646490","wikidata":"https://www.wikidata.org/wiki/Q25203551","display_name":"Clinical phenotype","level":4,"score":0.4299767017364502},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4206872284412384},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3947394788265228},{"id":"https://openalex.org/C127716648","wikidata":"https://www.wikidata.org/wiki/Q104053","display_name":"Phenotype","level":3,"score":0.36166149377822876},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33664003014564514},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.11074379086494446},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.08593970537185669},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.06729260087013245},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2808719.2808741","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2808719.2808741","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41999998688697815,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W66838807","https://openalex.org/W85058473","https://openalex.org/W166926187","https://openalex.org/W1547132634","https://openalex.org/W1661328078","https://openalex.org/W1851720369","https://openalex.org/W1902027874","https://openalex.org/W1969116741","https://openalex.org/W1973253383","https://openalex.org/W1973445088","https://openalex.org/W1973825638","https://openalex.org/W1975058220","https://openalex.org/W1976526581","https://openalex.org/W2007426484","https://openalex.org/W2011064969","https://openalex.org/W2021787191","https://openalex.org/W2027106132","https://openalex.org/W2041389007","https://openalex.org/W2046817886","https://openalex.org/W2050569380","https://openalex.org/W2053080232","https://openalex.org/W2054394099","https://openalex.org/W2054396560","https://openalex.org/W2057096224","https://openalex.org/W2070073456","https://openalex.org/W2075779886","https://openalex.org/W2075940779","https://openalex.org/W2100495367","https://openalex.org/W2101086247","https://openalex.org/W2114153178","https://openalex.org/W2121382432","https://openalex.org/W2122825543","https://openalex.org/W2136922672","https://openalex.org/W2139796029","https://openalex.org/W2153635508","https://openalex.org/W2158939484","https://openalex.org/W2163922914","https://openalex.org/W2187089797","https://openalex.org/W2295582178","https://openalex.org/W2322002063","https://openalex.org/W2323830513","https://openalex.org/W2501238810","https://openalex.org/W2549349192","https://openalex.org/W2606321545","https://openalex.org/W2741951152","https://openalex.org/W2997183031","https://openalex.org/W3040793723","https://openalex.org/W4233045210","https://openalex.org/W6602739985"],"related_works":["https://openalex.org/W3164771895","https://openalex.org/W2604464132","https://openalex.org/W29071608","https://openalex.org/W2161088626","https://openalex.org/W3029893540","https://openalex.org/W2314682585","https://openalex.org/W2313584493","https://openalex.org/W2135667114","https://openalex.org/W2110968082","https://openalex.org/W3122747281"],"abstract_inverted_index":{"With":[0],"the":[1,4,8,58,67,98,102,126,161,164,187,190,194,199,251,267,295],"expansion":[2],"of":[3,11,28,69,92,101,128,183,186,231,269,277,280],"healthcare":[5,18],"industry":[6],"and":[7,20,76,119,139,149,158,177,285],"overwhelming":[9],"amount":[10],"electronic":[12,83],"health":[13,84],"records":[14,85],"(EHRs)":[15],"shared":[16],"by":[17,234,255,259],"institutions":[19],"practitioners,":[21],"we":[22,65],"now":[23],"wish":[24],"to":[25,31,56,136,219],"take":[26],"advantage":[27],"EHR":[29,175,204,221],"data":[30,205],"develop":[32],"an":[33],"effective":[34],"disease":[35,43,60,94],"risk":[36,72,95,111,133,208,245,252,296,304],"management":[37],"model":[38,218],"that":[39],"not":[40,292],"only":[41,293],"improve":[42,89],"prediction":[44,79,297],"but":[45,154,299],"also":[46,300],"shows":[47],"clinically":[48,152,302],"meaningful":[49,303],"feature":[50,201],"grouping":[51,207,306],"which":[52,142,226],"can":[53],"be":[54,151,170],"used":[55],"define":[57],"bone":[59,77,93,104,140,286,308],"phenotypes.":[61],"In":[62],"this":[63],"paper,":[64],"explore":[66],"feasibility":[68],"extracting":[70],"critical":[71],"factors":[73,112,134,209],"for":[74,206,210,307],"osteoporosis":[75,138,284],"fracture":[78,287],"based":[80],"on":[81,124,272],"heterogeneous":[82],"(EHRs).":[86],"This":[87,242],"will":[88,248],"our":[90,270],"understanding":[91],"arising":[96],"from":[97,198,203],"complex":[99],"interplay":[100],"human":[103,224],"mineral":[105],"density":[106],"(BMD)":[107],"assessment":[108],"with":[109,147,222],"major":[110],"such":[113],"as":[114],"gender,":[115],"age,":[116],"family":[117],"history,":[118],"life":[120],"styles.":[121],"We":[122,192,212,265],"focus":[123],"addressing":[125],"problem":[127],"identifying":[129,184],"individual":[130],"or":[131],"integrated":[132,290],"(RFs)":[135],"predict":[137],"fractures,":[141],"are":[143],"common":[144],"diseases":[145],"associated":[146],"aging":[148],"may":[150],"silent":[153],"cause":[155],"significant":[156],"mortality":[157],"morbidity.":[159],"On":[160],"other":[162],"hand,":[163],"unbiased,":[165],"EHR-driven":[166],"phenotype":[167],"discovery":[168],"could":[169],"achieved":[171],"using":[172],"a":[173,178,214,228,238,262,273],"massive":[174],"dataset":[176,282],"computationally":[179],"intense":[180],"analysis":[181],"capable":[182],"all":[185],"phenotypes":[188],"in":[189,237],"dataset.":[191],"infer":[193],"precise":[195],"phenotypic":[196],"patterns":[197],"new":[200,229,243],"representation":[202,230,247,291],"osteoporosis.":[211],"present":[213,250],"2-layer":[215],"deep":[216],"graphical":[217],"use":[220],"minimal":[223],"supervision":[225],"derives":[227],"medical":[232],"objects":[233],"embedding":[235],"them":[236],"low-dimensional":[239,244],"vector":[240],"space.":[241],"factor":[246,253,305],"ultimately":[249],"embedding/clustering":[254],"offering":[256],"intuitive":[257],"visualization":[258],"projection":[260],"onto":[261],"2D":[263],"plane.":[264],"demonstrate":[266],"capability":[268],"framework":[271],"9704":[274],"Caucasian":[275],"women":[276],"20":[278],"years":[279],"prospective":[281],"under":[283],"assessment.":[288],"The":[289],"improves":[294],"accuracy":[298],"presents":[301],"diseases.":[309]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}