{"id":"https://openalex.org/W2575010539","doi":null,"title":"Bayesian nonparametric collaborative topic Poisson factorization for electronic health records-based phenotyping","display_name":"Bayesian nonparametric collaborative topic Poisson factorization for electronic health records-based phenotyping","publication_year":2016,"publication_date":"2016-07-09","ids":{"openalex":"https://openalex.org/W2575010539","mag":"2575010539"},"language":"en","primary_location":{"id":"mag:2575010539","doi":null,"is_oa":false,"landing_page_url":"http://dblp.uni-trier.de/db/conf/ijcai/ijcai2016.html#LeeLKM16","pdf_url":null,"source":{"id":"https://openalex.org/S4306419999","display_name":"International Joint Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Joint Conference on Artificial Intelligence","raw_type":null},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":[],"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/A5037032450","display_name":"Wonsung Lee","orcid":"https://orcid.org/0009-0000-5126-9331","observed_orcids":["https://orcid.org/0009-0000-5126-9331"]},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Wonsung Lee","raw_affiliation_strings":["Department of Industrial and Systems Engineerning, KAIST, Daejeon, Republic of Korea#TAB#"],"raw_orcid":"https://orcid.org/0009-0000-5126-9331","affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineerning, KAIST, Daejeon, Republic of Korea#TAB#","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100785331","display_name":"Youngmin Lee","orcid":"https://orcid.org/0000-0001-8064-9149","observed_orcids":["https://orcid.org/0000-0001-8064-9149"]},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Youngmin Lee","raw_affiliation_strings":["Department of Industrial and Systems Engineerning, KAIST, Daejeon, Republic of Korea#TAB#"],"raw_orcid":"https://orcid.org/0000-0001-8064-9149","affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineerning, KAIST, Daejeon, Republic of Korea#TAB#","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100716622","display_name":"Heeyoung Kim","orcid":"https://orcid.org/0000-0001-6415-9887","observed_orcids":["https://orcid.org/0000-0001-6415-9887"]},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Heeyoung Kim","raw_affiliation_strings":["Department of Industrial and Systems Engineerning, KAIST, Daejeon, Republic of Korea#TAB#"],"raw_orcid":"https://orcid.org/0000-0001-6415-9887","affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineerning, KAIST, Daejeon, Republic of Korea#TAB#","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017589963","display_name":"Il\u2010Chul Moon","orcid":"https://orcid.org/0000-0002-1798-1306","observed_orcids":["https://orcid.org/0000-0002-1798-1306"]},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Il\u2010Chul Moon","raw_affiliation_strings":["Department of Industrial and Systems Engineerning, KAIST, Daejeon, Republic of Korea#TAB#"],"raw_orcid":"https://orcid.org/0000-0002-1798-1306","affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineerning, KAIST, Daejeon, Republic of Korea#TAB#","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I157485424"],"apc_list":null,"apc_paid":null,"fwci":0.6482,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.68910373,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2544","last_page":"2552"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9922000169754028,"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":0.9922000169754028,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.002199999988079071,"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/T10350","display_name":"Electronic Health Records Systems","score":0.0003000000142492354,"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/electronic-health-records","display_name":"electronic health records","score":0.843999981880188},{"id":"https://openalex.org/keywords/phenotyping","display_name":"phenotyping","score":0.9049999713897705},{"id":"https://openalex.org/keywords/nonparametric-bayesian-inference","display_name":"Bayesian nonparametrics","score":0.8140000104904175},{"id":"https://openalex.org/keywords/topic-modeling","display_name":"topic modeling","score":0.75},{"id":"https://openalex.org/keywords/matrix-factorization","display_name":"matrix factorization","score":0.7540000081062317},{"id":"https://openalex.org/keywords/stochastic-variational-inference","display_name":"stochastic variational inference","score":0.8059999942779541},{"id":"https://openalex.org/keywords/disease-subtypes","display_name":"disease subtypes","score":0.6119999885559082},{"id":"https://openalex.org/keywords/patient-demographics","display_name":"patient demographics","score":0.5199999809265137}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6915439367294312},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.5951030850410461},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5772151947021484},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.5698790550231934},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5529037117958069},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5359865427017212},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5183988213539124},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5000929832458496},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.4813573956489563},{"id":"https://openalex.org/C3019952477","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Health records","level":3,"score":0.4748530685901642},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.43832236528396606},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.4183548092842102},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3632844090461731},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.22724184393882751},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1901724934577942},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15753424167633057},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.11779335141181946},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.08655545115470886},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:2575010539","doi":null,"is_oa":false,"landing_page_url":"http://dblp.uni-trier.de/db/conf/ijcai/ijcai2016.html#LeeLKM16","pdf_url":null,"source":{"id":"https://openalex.org/S4306419999","display_name":"International Joint Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Joint Conference on Artificial Intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.6240000128746033}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1827931243","https://openalex.org/W1880262756","https://openalex.org/W1969116741","https://openalex.org/W1972588194","https://openalex.org/W1973825638","https://openalex.org/W1986966428","https://openalex.org/W1998249118","https://openalex.org/W2014556601","https://openalex.org/W2027106132","https://openalex.org/W2054141820","https://openalex.org/W2064337796","https://openalex.org/W2065594991","https://openalex.org/W2079196112","https://openalex.org/W2121382432","https://openalex.org/W2123528936","https://openalex.org/W2125261539","https://openalex.org/W2132927459","https://openalex.org/W2132996843","https://openalex.org/W2135790056","https://openalex.org/W2151068025","https://openalex.org/W2151967501","https://openalex.org/W2158266063","https://openalex.org/W2161353674","https://openalex.org/W2165037395","https://openalex.org/W2166851633","https://openalex.org/W2167032822","https://openalex.org/W3122242054"],"related_works":["https://openalex.org/W4294052933","https://openalex.org/W4290944545","https://openalex.org/W4417467455","https://openalex.org/W2541242421","https://openalex.org/W2984675714","https://openalex.org/W2556399337","https://openalex.org/W2754794949","https://openalex.org/W7127080584","https://openalex.org/W3012523953","https://openalex.org/W2982606431"],"abstract_inverted_index":{"Phenotyping":[0],"with":[1,52,131],"electronic":[2],"health":[3],"records":[4],"(EHR)":[5],"has":[6],"received":[7],"much":[8],"attention":[9],"in":[10,121],"recent":[11],"years":[12],"because":[13],"the":[14,41,82,96,108,113,123,129,153],"phenotyping":[15,59,79],"opens":[16],"a":[17,140,162,172],"new":[18],"way":[19],"to":[20,171],"discover":[21],"clinically":[22],"meaningful":[23],"insights,":[24],"such":[25],"as":[26],"disease":[27,30],"progression":[28],"and":[29,62,71,102,111,135,143],"subtypes":[31],"without":[32],"human":[33],"supervisions.":[34],"In":[35],"spite":[36],"of":[37,44,105],"its":[38,144],"potential":[39],"benefits,":[40],"complex":[42],"nature":[43],"EHR":[45,174],"often":[46],"requires":[47],"more":[48],"sophisticated":[49],"methodologies":[50],"compared":[51,128],"traditional":[53],"methods.":[54],"Previous":[55],"works":[56],"on":[57,152],"EHR-based":[58,78],"utilized":[60],"unsupervised":[61],"supervised":[63],"learning":[64],"methods":[65,138],"separately":[66],"by":[67,80,156,168],"independently":[68],"detecting":[69],"phenotypes":[70],"predicting":[72,122],"medical":[73],"risk":[74,115,124],"scores.":[75,116],"To":[76],"improve":[77],"bridging":[81],"separated":[83],"methods,":[84],"we":[85,127,160],"present":[86],"Bayesian":[87],"nonparametric":[88,98],"collaborative":[89,145],"topic":[90,136],"Poisson":[91,100,141],"factorization":[92,101,134,142],"(BN-CTPF)":[93],"that":[94],"is":[95],"first":[97,103],"content-based":[99],"application":[104],"jointly":[106],"analyzing":[107],"phenotye":[109],"topics":[110,155],"estimating":[112],"individual":[114],"BN-CTPF":[117,148,170],"shows":[118],"better":[119],"performances":[120],"scores":[125],"when":[126],"model":[130],"previous":[132],"matrix":[133],"modeling":[137],"including":[139],"extensions.":[146],"Also,":[147],"provides":[149],"faceted":[150],"views":[151],"phenotype":[154],"patients'":[157],"demographics.":[158],"Finally,":[159],"demonstrate":[161],"scalable":[163],"stochastic":[164],"variational":[165],"inference":[166],"algorithm":[167],"applying":[169],"national-scale":[173],"dataset.":[175]},"counts_by_year":[{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2017-01-26T00:00:00"}