{"id":"https://openalex.org/W7124134553","doi":"https://doi.org/10.1145/3777577.3777707","title":"Toward the use of multi-task learning for entity recognition and normalization of Chinese disease symptoms","display_name":"Toward the use of multi-task learning for entity recognition and normalization of Chinese disease symptoms","publication_year":2025,"publication_date":"2025-10-24","ids":{"openalex":"https://openalex.org/W7124134553","doi":"https://doi.org/10.1145/3777577.3777707"},"language":null,"primary_location":{"id":"doi:10.1145/3777577.3777707","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3777577.3777707","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 6th International Symposium on Artificial Intelligence for Medical Sciences","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3777577.3777707","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5123050820","display_name":"Bangtai Qu","orcid":null},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Bangtai Qu","raw_affiliation_strings":["Institute of Medical Informatics, National Cheng Kung University, Taiwan, China"],"affiliations":[{"raw_affiliation_string":"Institute of Medical Informatics, National Cheng Kung University, Taiwan, China","institution_ids":["https://openalex.org/I91807558"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5122996378","display_name":"Kunchan Lan","orcid":null},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Kunchan Lan","raw_affiliation_strings":["Institute of Medical Informatics, National Cheng Kung University, Taiwan, China"],"affiliations":[{"raw_affiliation_string":"Institute of Medical Informatics, National Cheng Kung University, Taiwan, China","institution_ids":["https://openalex.org/I91807558"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5123050820"],"corresponding_institution_ids":["https://openalex.org/I91807558"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.85888006,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"802","last_page":"810"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.5990999937057495,"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/T10028","display_name":"Topic Modeling","score":0.5990999937057495,"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":0.17640000581741333,"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":0.04479999840259552,"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/normalization","display_name":"Normalization (sociology)","score":0.6952999830245972},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.41019999980926514},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.3815000057220459},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.3458999991416931},{"id":"https://openalex.org/keywords/health-informatics","display_name":"Health informatics","score":0.3391999900341034},{"id":"https://openalex.org/keywords/named-entity-recognition","display_name":"Named-entity recognition","score":0.33719998598098755},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.3319000005722046},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.32670000195503235}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7436000108718872},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.6952999830245972},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.623199999332428},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5648000240325928},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5570999979972839},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.41019999980926514},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.3815000057220459},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.3458999991416931},{"id":"https://openalex.org/C145642194","wikidata":"https://www.wikidata.org/wiki/Q870895","display_name":"Health informatics","level":3,"score":0.3391999900341034},{"id":"https://openalex.org/C2779135771","wikidata":"https://www.wikidata.org/wiki/Q403574","display_name":"Named-entity recognition","level":3,"score":0.33719998598098755},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3319000005722046},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.32670000195503235},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.31220000982284546},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.30979999899864197},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.30169999599456787},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.29750001430511475},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C69505689","wikidata":"https://www.wikidata.org/wiki/Q455338","display_name":"Unified Medical Language System","level":2,"score":0.2754000127315521},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.274399995803833},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.27140000462532043},{"id":"https://openalex.org/C73301696","wikidata":"https://www.wikidata.org/wiki/Q5469984","display_name":"Formalism (music)","level":3,"score":0.27079999446868896},{"id":"https://openalex.org/C191630685","wikidata":"https://www.wikidata.org/wiki/Q4027615","display_name":"Informatics","level":2,"score":0.2689000070095062},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2603999972343445},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.25429999828338623},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.25360000133514404}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3777577.3777707","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3777577.3777707","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 6th International Symposium on Artificial Intelligence for Medical Sciences","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3777577.3777707","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3777577.3777707","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 6th International Symposium on Artificial Intelligence for Medical Sciences","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5936413407325745}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2952595356","https://openalex.org/W2963558486","https://openalex.org/W3043710593","https://openalex.org/W3173333551","https://openalex.org/W3173628900","https://openalex.org/W3176095518","https://openalex.org/W4206505934","https://openalex.org/W4226470037","https://openalex.org/W4366465368"],"related_works":[],"abstract_inverted_index":{"Multi-task":[0],"learning":[1],"(MTL)":[2],"offers":[3],"a":[4,42,53,123,142],"powerful":[5],"paradigm":[6],"for":[7,101,148,166,170],"jointly":[8],"solving":[9],"correlated":[10],"natural":[11],"language":[12],"processing":[13],"(NLP)":[14],"tasks,":[15],"but":[16],"its":[17],"effectiveness":[18],"is":[19],"often":[20],"hindered":[21],"by":[22],"suboptimal":[23],"loss":[24,57,195],"balancing,":[25,196],"data":[26,85,104],"scarcity,":[27],"and":[28,77,87,106,150,168,200],"complex":[29],"linguistic":[30],"structures":[31,115],"like":[32],"nested":[33,113],"entities.":[34],"To":[35],"address":[36],"these":[37],"fundamental":[38],"challenges,":[39],"we":[40,51,93,121],"propose":[41],"novel":[43],"MTL":[44,205],"framework":[45,98,140],"with":[46,161],"significant":[47],"methodological":[48],"advancements.":[49],"First,":[50],"introduce":[52],"trainable":[54],"weighted":[55],"joint":[56,125],"strategy":[58],"that":[59,128],"dynamically":[60],"optimizes":[61],"the":[62,173],"contribution":[63],"of":[64],"each":[65],"task":[66],"during":[67],"training,":[68],"achieving":[69],"better":[70],"equilibrium":[71],"between":[72],"Medical":[73,78],"Entity":[74,79],"Recognition":[75],"(MER)":[76],"Normalization":[80],"(MEN).":[81],"Second,":[82],"to":[83,90,110,133,184],"combat":[84],"scarcity":[86],"enhance":[88],"generalization":[89],"unseen":[91],"examples,":[92],"develop":[94],"an":[95],"LLM-driven":[96],"pseudo-labeling":[97],"using":[99],"ChatGPT":[100],"high-quality":[102],"synthetic":[103],"generation":[105],"iterative":[107],"self-training.":[108],"Third,":[109],"explicitly":[111],"model":[112],"entity":[114],"prevalent":[116],"in":[117,207],"Chinese":[118,145,174,185],"medical":[119,146,186],"text,":[120],"design":[122],"multi-level":[124],"labeling":[126],"scheme":[127],"extends":[129],"standard":[130],"sequence":[131],"tagging":[132],"capture":[134],"hierarchical":[135,201],"semantics.":[136],"We":[137],"validate":[138],"our":[139],"on":[141,172],"newly":[143],"curated":[144],"dataset":[147,175],"MER":[149,167],"MEN.":[151],"Experimental":[152],"results":[153],"demonstrate":[154],"substantial":[155],"performance":[156],"improvements":[157],"over":[158],"strong":[159],"baselines,":[160],"F1":[162],"scores":[163],"reaching":[164],"91.28%":[165],"90.99%":[169],"MEN":[171],"after":[176],"full":[177],"optimization.":[178],"Our":[179],"work":[180],"contributes":[181],"not":[182],"only":[183],"informatics":[187],"but,":[188],"more":[189],"importantly,":[190],"provides":[191],"generalizable":[192],"technical":[193],"solutions\u2014dynamic":[194],"LLM-based":[197],"semi-supervised":[198],"learning,":[199],"labeling\u2014for":[202],"complex,":[203],"low-resource":[204],"scenarios":[206],"NLP.":[208]},"counts_by_year":[],"updated_date":"2026-01-15T23:21:31.212559","created_date":"2026-01-15T00:00:00"}