{"id":"https://openalex.org/W3035294872","doi":"https://doi.org/10.24963/ijcai.2020/461","title":"A Label Attention Model for ICD Coding from Clinical Text","display_name":"A Label Attention Model for ICD Coding from Clinical Text","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3035294872","doi":"https://doi.org/10.24963/ijcai.2020/461","mag":"3035294872"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2020/461","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/461","pdf_url":"https://www.ijcai.org/proceedings/2020/0461.pdf","source":null,"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2020/0461.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102711710","display_name":"Thanh Vu","orcid":"https://orcid.org/0009-0009-4565-4853"},"institutions":[{"id":"https://openalex.org/I1292875679","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07","country_code":"AU","type":"government","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I4210141844","display_name":"Australian e-Health Research Centre","ror":"https://ror.org/04ywhbc61","country_code":"AU","type":"facility","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801244131","https://openalex.org/I2801453606","https://openalex.org/I4210141844","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Thanh Vu","raw_affiliation_strings":["Australian e-Health Research Centre, CSIRO, Brisbane, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Australian e-Health Research Centre, CSIRO, Brisbane, Australia","institution_ids":["https://openalex.org/I4210141844","https://openalex.org/I1292875679"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063933953","display_name":"Dat Quoc Nguyen","orcid":"https://orcid.org/0000-0001-8214-2878"},"institutions":[{"id":"https://openalex.org/I4210142044","display_name":"VinUniversity","ror":"https://ror.org/052dmdr17","country_code":"VN","type":"education","lineage":["https://openalex.org/I4210142044"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Dat Quoc Nguyen","raw_affiliation_strings":["VinAI Research, Hanoi, Vietnam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"VinAI Research, Hanoi, Vietnam","institution_ids":["https://openalex.org/I4210142044"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023213398","display_name":"Anthony Nguyen","orcid":"https://orcid.org/0000-0002-6215-6954"},"institutions":[{"id":"https://openalex.org/I1292875679","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07","country_code":"AU","type":"government","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I4210141844","display_name":"Australian e-Health Research Centre","ror":"https://ror.org/04ywhbc61","country_code":"AU","type":"facility","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801244131","https://openalex.org/I2801453606","https://openalex.org/I4210141844","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Anthony Nguyen","raw_affiliation_strings":["Australian e-Health Research Centre, CSIRO, Brisbane, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Australian e-Health Research Centre, CSIRO, Brisbane, Australia","institution_ids":["https://openalex.org/I4210141844","https://openalex.org/I1292875679"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102711710"],"corresponding_institution_ids":["https://openalex.org/I1292875679","https://openalex.org/I4210141844"],"apc_list":null,"apc_paid":null,"fwci":6.6682,"has_fulltext":false,"cited_by_count":146,"citation_normalized_percentile":{"value":0.97818095,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3335","last_page":"3341"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9829999804496765,"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"}},"topics":[{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9829999804496765,"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"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9824000000953674,"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/T14400","display_name":"Medical Coding and Health Information","score":0.98089998960495,"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/computer-science","display_name":"Computer science","score":0.7791180610656738},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.6691188812255859},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5915365815162659},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.551710307598114},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5188763737678528},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5183202028274536},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.45315927267074585},{"id":"https://openalex.org/keywords/medical-classification","display_name":"Medical classification","score":0.4355807602405548},{"id":"https://openalex.org/keywords/icd-10","display_name":"ICD-10","score":0.4205886721611023},{"id":"https://openalex.org/keywords/convolutional-code","display_name":"Convolutional code","score":0.4112916588783264},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3430478572845459},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.3109015226364136},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1579781472682953}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7791180610656738},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.6691188812255859},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5915365815162659},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.551710307598114},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5188763737678528},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5183202028274536},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.45315927267074585},{"id":"https://openalex.org/C154874363","wikidata":"https://www.wikidata.org/wiki/Q3518464","display_name":"Medical classification","level":2,"score":0.4355807602405548},{"id":"https://openalex.org/C2781116378","wikidata":"https://www.wikidata.org/wiki/Q45127","display_name":"ICD-10","level":2,"score":0.4205886721611023},{"id":"https://openalex.org/C157899210","wikidata":"https://www.wikidata.org/wiki/Q1395022","display_name":"Convolutional code","level":3,"score":0.4112916588783264},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3430478572845459},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.3109015226364136},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1579781472682953},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C159110408","wikidata":"https://www.wikidata.org/wiki/Q121176","display_name":"Nursing","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.24963/ijcai.2020/461","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/461","pdf_url":"https://www.ijcai.org/proceedings/2020/0461.pdf","source":null,"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2007.06351","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2007.06351","pdf_url":"https://arxiv.org/pdf/2007.06351","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2020/461","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/461","pdf_url":"https://www.ijcai.org/proceedings/2020/0461.pdf","source":null,"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17","score":0.550000011920929}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3035294872.pdf","grobid_xml":"https://content.openalex.org/works/W3035294872.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1532325895","https://openalex.org/W1832693441","https://openalex.org/W1974957625","https://openalex.org/W1989568037","https://openalex.org/W1997057722","https://openalex.org/W2064078928","https://openalex.org/W2096664202","https://openalex.org/W2104321900","https://openalex.org/W2157331557","https://openalex.org/W2396881363","https://openalex.org/W2470673105","https://openalex.org/W2597655663","https://openalex.org/W2739515596","https://openalex.org/W2768948924","https://openalex.org/W2798935874","https://openalex.org/W2908510526","https://openalex.org/W2941736751","https://openalex.org/W2950133940","https://openalex.org/W2950635152","https://openalex.org/W2951008357","https://openalex.org/W2951125449","https://openalex.org/W2963912736","https://openalex.org/W2964015378","https://openalex.org/W2964121744","https://openalex.org/W2964142373","https://openalex.org/W2970971581","https://openalex.org/W2976922584","https://openalex.org/W2985173696","https://openalex.org/W2997050424","https://openalex.org/W4247198512","https://openalex.org/W4288101924","https://openalex.org/W4293582125","https://openalex.org/W4294170691","https://openalex.org/W4295312788"],"related_works":["https://openalex.org/W106077315","https://openalex.org/W4385264896","https://openalex.org/W1988558550","https://openalex.org/W4385567952","https://openalex.org/W387410332","https://openalex.org/W4400769461","https://openalex.org/W147366512","https://openalex.org/W4292539280","https://openalex.org/W4377564205","https://openalex.org/W4362682139"],"abstract_inverted_index":{"ICD":[0,48,75,106,120,130],"coding":[1],"is":[2,31],"a":[3,60,99,146],"process":[4,24],"of":[5,10,86,118,129],"assigning":[6],"the":[7,39,66,84,89,112,116,119,127,138,158,161,165,181,187],"International":[8],"Classification":[9],"Disease":[11],"diagnosis":[12],"codes":[13,76,131],"to":[14,35,74,83,137,156],"clinical/medical":[15],"notes":[16],"documented":[17],"by":[18],"health":[19],"professionals":[20],"(e.g.":[21],"clinicians).":[22],"This":[23],"requires":[25],"significant":[26],"human":[27],"resources,":[28],"and":[29,33,68,115,180],"thus":[30],"costly":[32],"prone":[34],"error.":[36],"To":[37],"handle":[38,110,157],"problem,":[40],"machine":[41],"learning":[42,149,183],"has":[43],"been":[44],"utilized":[45],"for":[46,104,189],"automatic":[47,105],"coding.":[49],"Previous":[50],"state-of-the-art":[51,173],"models":[52],"were":[53],"based":[54],"on":[55,175],"convolutional":[56],"neural":[57],"networks,":[58],"using":[59,160],"single/several":[61],"fixed":[62],"window":[63,91],"sizes.":[64],"However,":[65],"lengths":[67,114],"interdependence":[69,117],"between":[70],"text":[71,79,123],"fragments":[72],"related":[73,122],"in":[77],"clinical":[78],"vary":[80],"significantly,":[81],"leading":[82,136],"difficulty":[85],"deciding":[87],"what":[88],"best":[90],"sizes":[92],"are.":[93],"In":[94],"this":[95],"paper,":[96],"we":[97,143],"propose":[98,145],"new":[100,172],"label":[101,153,168],"attention":[102,154,169],"model":[103,155,170],"coding,":[107],"which":[108],"can":[109],"both":[111],"various":[113],"code":[121],"fragments.":[124],"Furthermore,":[125],"as":[126],"majority":[128],"are":[132],"not":[133],"frequently":[134],"used,":[135],"extremely":[139],"imbalanced":[140],"data":[141],"issue,":[142,159],"additionally":[144],"hierarchical":[147,162],"joint":[148,182],"mechanism":[150,184],"extending":[151],"our":[152],"relationships":[163],"among":[164],"codes.":[166,191],"Our":[167],"achieves":[171],"results":[174],"three":[176],"benchmark":[177],"MIMIC":[178],"datasets,":[179],"helps":[185],"improve":[186],"performances":[188],"infrequent":[190]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":30},{"year":2024,"cited_by_count":33},{"year":2023,"cited_by_count":29},{"year":2022,"cited_by_count":24},{"year":2021,"cited_by_count":27}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}