{"id":"https://openalex.org/W3196387851","doi":"https://doi.org/10.1145/3459930.3469547","title":"DeepNote-GNN","display_name":"DeepNote-GNN","publication_year":2021,"publication_date":"2021-07-30","ids":{"openalex":"https://openalex.org/W3196387851","doi":"https://doi.org/10.1145/3459930.3469547","mag":"3196387851"},"language":"en","primary_location":{"id":"doi:10.1145/3459930.3469547","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459930.3469547","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th ACM International 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/A5033075851","display_name":"Sara Nouri Golmaei","orcid":null},"institutions":[{"id":"https://openalex.org/I55769427","display_name":"Indiana University \u2013 Purdue University Indianapolis","ror":"https://ror.org/05gxnyn08","country_code":"US","type":"education","lineage":["https://openalex.org/I55769427","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sara Nouri Golmaei","raw_affiliation_strings":["IUPUI"],"affiliations":[{"raw_affiliation_string":"IUPUI","institution_ids":["https://openalex.org/I55769427"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038978057","display_name":"Xiao Luo","orcid":"https://orcid.org/0000-0002-3649-9785"},"institutions":[{"id":"https://openalex.org/I55769427","display_name":"Indiana University \u2013 Purdue University Indianapolis","ror":"https://ror.org/05gxnyn08","country_code":"US","type":"education","lineage":["https://openalex.org/I55769427","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiao Luo","raw_affiliation_strings":["IUPUI"],"affiliations":[{"raw_affiliation_string":"IUPUI","institution_ids":["https://openalex.org/I55769427"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5033075851"],"corresponding_institution_ids":["https://openalex.org/I55769427"],"apc_list":null,"apc_paid":null,"fwci":3.9125,"has_fulltext":false,"cited_by_count":36,"citation_normalized_percentile":{"value":0.94563446,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9994999766349792,"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":0.9994999766349792,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9936000108718872,"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"}},{"id":"https://openalex.org/T10144","display_name":"Blood Pressure and Hypertension Studies","score":0.9764999747276306,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7495160698890686},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7026097774505615},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.7009235620498657},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.698775053024292},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6153431534767151},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.6019685864448547},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5014746189117432},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.44864708185195923},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.41978755593299866},{"id":"https://openalex.org/keywords/health-records","display_name":"Health records","score":0.4124397933483124},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.3868688642978668},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.339682400226593},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09049421548843384}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7495160698890686},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7026097774505615},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.7009235620498657},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.698775053024292},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6153431534767151},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.6019685864448547},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5014746189117432},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.44864708185195923},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.41978755593299866},{"id":"https://openalex.org/C3019952477","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Health records","level":3,"score":0.4124397933483124},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.3868688642978668},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.339682400226593},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09049421548843384},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3459930.3469547","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459930.3469547","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.47999998927116394,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W109419940","https://openalex.org/W1980867644","https://openalex.org/W2004512400","https://openalex.org/W2054860584","https://openalex.org/W2079735306","https://openalex.org/W2086923543","https://openalex.org/W2102344329","https://openalex.org/W2116341502","https://openalex.org/W2131571251","https://openalex.org/W2134127699","https://openalex.org/W2137080502","https://openalex.org/W2148860680","https://openalex.org/W2176412452","https://openalex.org/W2250539671","https://openalex.org/W2309139110","https://openalex.org/W2396881363","https://openalex.org/W2557074642","https://openalex.org/W2625625371","https://openalex.org/W2800167607","https://openalex.org/W2805089815","https://openalex.org/W2895763047","https://openalex.org/W2905279144","https://openalex.org/W2911489562","https://openalex.org/W2921297510","https://openalex.org/W2923546398","https://openalex.org/W2937845937","https://openalex.org/W2963341956","https://openalex.org/W2963650911","https://openalex.org/W2997419538","https://openalex.org/W3002510506","https://openalex.org/W3004530661","https://openalex.org/W3011483410","https://openalex.org/W3011681336","https://openalex.org/W3128451008","https://openalex.org/W4231753770"],"related_works":["https://openalex.org/W4225394202","https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W1847088711","https://openalex.org/W3036642985","https://openalex.org/W3032952384","https://openalex.org/W3008584592","https://openalex.org/W2968295315","https://openalex.org/W4387022695","https://openalex.org/W3034267371"],"abstract_inverted_index":{"With":[0],"the":[1,62,175,184,195,199,207,212,233,246],"increasing":[2],"availability":[3],"of":[4,35,61,75,125,136,146,216,219],"Electronic":[5],"Health":[6],"Records":[7],"(EHRs)":[8],"and":[9,48,88,106,129,166,214,236,240],"advances":[10],"in":[11,30,43],"deep":[12,16,97,121,134,159],"learning":[13,51,98,122],"techniques,":[14],"developing":[15],"predictive":[17,37,67],"models":[18,38],"that":[19,77,101,188,225],"use":[20],"EHR":[21,44],"data":[22,42,84],"to":[23,111,173,194,210,232],"solve":[24],"healthcare":[25],"problems":[26],"has":[27,228],"gained":[28],"momentum":[29],"recent":[31],"years.":[32],"The":[33,221],"majority":[34],"clinical":[36,52,86,103,137],"benefit":[39],"from":[40,54],"structured":[41],"(e.g.,":[45,85],"lab":[46],"measurements":[47],"medications).":[49],"Still,":[50],"outcomes":[53],"all":[55],"possible":[56],"information":[57,76,105],"sources":[58,74],"is":[59,118,164,171,238],"one":[60],"main":[63],"challenges":[64],"when":[65],"building":[66],"models.":[68],"This":[69],"work":[70],"focuses":[71],"on":[72,144,183,198,245],"two":[73,126],"have":[78],"been":[79],"underused":[80],"by":[81],"researchers;":[82],"unstructured":[83],"notes)":[87],"a":[89,94,119,140,147,161,229],"patient":[90,107,130,162,226],"network.":[91,131],"We":[92,204],"propose":[93],"novel":[95],"hybrid":[96],"model,":[99],"DeepNote-GNN,":[100],"integrates":[102],"notes":[104,138],"network":[108,163,176,227],"topological":[109],"structure":[110],"improve":[112],"30-day":[113,200,247],"hospital":[114,178,201],"readmission":[115,179,202,248],"prediction.":[116],"DeepNote-GNN":[117,189,208,237],"robust":[120,239],"framework":[123],"consisting":[124],"modules:":[127],"DeepNote":[128,132],"extracts":[133],"representations":[135],"using":[139],"feature":[141],"aggregation":[142],"unit":[143],"top":[145],"state-of-the-art":[148,196],"Natural":[149],"Language":[150],"Processing":[151],"(NLP)":[152],"technique":[153],"-":[154],"BERT.":[155],"By":[156],"exploiting":[157],"these":[158],"representations,":[160],"built,":[165],"Graph":[167],"Neural":[168],"Network":[169],"(GNN)":[170],"used":[172],"train":[174],"for":[177],"predictions.":[180],"Performance":[181],"evaluation":[182],"MIMIC-III":[185],"dataset":[186],"demonstrates":[187],"achieves":[190],"superior":[191],"results":[192],"compared":[193],"baselines":[197],"task.":[203,250],"extensively":[205],"analyze":[206],"model":[209,222],"illustrate":[211],"effectiveness":[213],"contribution":[215,231],"each":[217],"component":[218],"it.":[220],"analysis":[223],"shows":[224],"significant":[230],"overall":[234],"performance,":[235],"can":[241],"consistently":[242],"perform":[243],"well":[244],"prediction":[249]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2021-09-13T00:00:00"}
