{"id":"https://openalex.org/W2294508402","doi":"https://doi.org/10.1109/embc.2015.7319957","title":"Post-surgical complication prediction in the presence of low-rank missing data","display_name":"Post-surgical complication prediction in the presence of low-rank missing data","publication_year":2015,"publication_date":"2015-08-01","ids":{"openalex":"https://openalex.org/W2294508402","doi":"https://doi.org/10.1109/embc.2015.7319957","mag":"2294508402","pmid":"https://pubmed.ncbi.nlm.nih.gov/26737857"},"language":"en","primary_location":{"id":"doi:10.1109/embc.2015.7319957","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2015.7319957","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref","pubmed"],"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/A5101110690","display_name":"Hang Wu","orcid":"https://orcid.org/0009-0008-6951-2211"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hang Wu","raw_affiliation_strings":["School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051940505","display_name":"Chih\u2010Wen Cheng","orcid":"https://orcid.org/0000-0002-3208-1795"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chihwen Cheng","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101039796","display_name":"Xiaoning Han","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210130930","display_name":"Peking University First Hospital","ror":"https://ror.org/02z1vqm45","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210130930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoning Han","raw_affiliation_strings":["Peking University First Hospital, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University First Hospital, Beijing, China","institution_ids":["https://openalex.org/I20231570","https://openalex.org/I4210130930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080427269","display_name":"Yong Huo","orcid":"https://orcid.org/0000-0002-5407-8773"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210130930","display_name":"Peking University First Hospital","ror":"https://ror.org/02z1vqm45","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210130930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Huo","raw_affiliation_strings":["Peking University First Hospital, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University First Hospital, Beijing, China","institution_ids":["https://openalex.org/I20231570","https://openalex.org/I4210130930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077858347","display_name":"Wenhui Ding","orcid":"https://orcid.org/0000-0001-7413-7884"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210130930","display_name":"Peking University First Hospital","ror":"https://ror.org/02z1vqm45","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210130930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhui Ding","raw_affiliation_strings":["Peking University First Hospital, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University First Hospital, Beijing, China","institution_ids":["https://openalex.org/I20231570","https://openalex.org/I4210130930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030096887","display_name":"May D. Wang","orcid":"https://orcid.org/0000-0003-3961-3608"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]},{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"May D. Wang","raw_affiliation_strings":["Department of Biomedical Engineering, Georgia Institute of Technology and Emory University and School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, Georgia Institute of Technology and Emory University and School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444","https://openalex.org/I150468666"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2057,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.49593731,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"227","issue":null,"first_page":"6808","last_page":"6811"},"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/T12303","display_name":"Tensor decomposition and applications","score":0.9879999756813049,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9807000160217285,"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/missing-data","display_name":"Missing data","score":0.9414239525794983},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6245610117912292},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.6100630760192871},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.5866812467575073},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5819869637489319},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.526641845703125},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.49124401807785034},{"id":"https://openalex.org/keywords/health-records","display_name":"Health records","score":0.46097153425216675},{"id":"https://openalex.org/keywords/matrix-completion","display_name":"Matrix completion","score":0.4560551345348358},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3266344368457794},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2622476816177368},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16469165682792664},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10775521397590637}],"concepts":[{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.9414239525794983},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6245610117912292},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.6100630760192871},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.5866812467575073},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5819869637489319},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.526641845703125},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.49124401807785034},{"id":"https://openalex.org/C3019952477","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Health records","level":3,"score":0.46097153425216675},{"id":"https://openalex.org/C2778459887","wikidata":"https://www.wikidata.org/wiki/Q6787865","display_name":"Matrix completion","level":3,"score":0.4560551345348358},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3266344368457794},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2622476816177368},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16469165682792664},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10775521397590637},{"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/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"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/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003627","descriptor_name":"Data Interpretation, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003627","descriptor_name":"Data Interpretation, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003627","descriptor_name":"Data Interpretation, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011183","descriptor_name":"Postoperative Complications","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D011183","descriptor_name":"Postoperative Complications","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D011183","descriptor_name":"Postoperative Complications","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D012372","descriptor_name":"ROC Curve","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012372","descriptor_name":"ROC Curve","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012372","descriptor_name":"ROC Curve","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D018570","descriptor_name":"Risk Assessment","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D018570","descriptor_name":"Risk Assessment","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D018570","descriptor_name":"Risk Assessment","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D057286","descriptor_name":"Electronic Health Records","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D057286","descriptor_name":"Electronic Health Records","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D057286","descriptor_name":"Electronic Health Records","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/embc.2015.7319957","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2015.7319957","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:26737857","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/26737857","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2689270938","display_name":null,"funder_award_id":"U54 CA 119338","funder_id":"https://openalex.org/F4320337351","funder_display_name":"National Cancer Institute"}],"funders":[{"id":"https://openalex.org/F4320337351","display_name":"National Cancer Institute","ror":"https://ror.org/040gcmg81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1499955781","https://openalex.org/W1891831556","https://openalex.org/W1990903627","https://openalex.org/W1995880999","https://openalex.org/W2054141820","https://openalex.org/W2065974896","https://openalex.org/W2072604363","https://openalex.org/W2099210013","https://openalex.org/W2122090912","https://openalex.org/W2135029798","https://openalex.org/W2137245235","https://openalex.org/W2160569988","https://openalex.org/W2163874082","https://openalex.org/W2611328865","https://openalex.org/W2963147719","https://openalex.org/W3143596294","https://openalex.org/W6675017388","https://openalex.org/W6677671969","https://openalex.org/W6680012447","https://openalex.org/W6680451568","https://openalex.org/W6683303121"],"related_works":["https://openalex.org/W4380150146","https://openalex.org/W3144354057","https://openalex.org/W4301205717","https://openalex.org/W4288107728","https://openalex.org/W2788210652","https://openalex.org/W3103289951","https://openalex.org/W3152273675","https://openalex.org/W2972830027","https://openalex.org/W3213035342","https://openalex.org/W3093503721"],"abstract_inverted_index":{"The":[0],"problem":[1],"of":[2,32,38,63,83,93],"missing":[3,43,55,64,84],"data":[4,56],"has":[5],"made":[6],"it":[7],"difficult":[8],"to":[9,52,58,69,77],"analyze":[10],"Electronic":[11],"Health":[12],"Records":[13],"(EHR).":[14],"In":[15],"EHR":[16],"data,":[17],"the":[18,23,81,91,106],"\"missingness\"":[19],"often":[20],"results":[21,99],"from":[22],"low-rank":[24,61],"property:":[25],"each":[26],"patient":[27],"is":[28],"considered":[29],"a":[30],"mixture":[31],"prototypical":[33],"patients,":[34],"and":[35,73,97],"certain":[36],"types":[37],"patients":[39],"will":[40],"have":[41],"similar":[42],"entries":[44],"in":[45,80,90],"their":[46],"records.":[47],"However,":[48],"most":[49],"existing":[50],"methods":[51,76,89],"deal":[53],"with":[54],"fail":[57],"capture":[59],"this":[60],"property":[62],"data.":[65,85],"Hence":[66],"we":[67],"propose":[68],"use":[70],"matrix":[71,74],"factorization":[72],"completion":[75],"perform":[78],"prediction":[79,96,107],"presence":[82],"We":[86],"validated":[87],"our":[88,102],"task":[92],"post-surgical":[94],"complication":[95],"experimental":[98],"show":[100],"that":[101],"method":[103],"can":[104],"improve":[105],"accuracy":[108],"significantly.":[109]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
