{"id":"https://openalex.org/W2970872015","doi":"https://doi.org/10.18653/v1/w19-5058","title":"NCUEE at MEDIQA 2019: Medical Text Inference Using Ensemble BERT-BiLSTM-Attention Model","display_name":"NCUEE at MEDIQA 2019: Medical Text Inference Using Ensemble BERT-BiLSTM-Attention Model","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2970872015","doi":"https://doi.org/10.18653/v1/w19-5058","mag":"2970872015"},"language":"en","primary_location":{"id":"doi:10.18653/v1/w19-5058","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w19-5058","pdf_url":"https://www.aclweb.org/anthology/W19-5058.pdf","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 18th BioNLP Workshop and Shared Task","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/W19-5058.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078362082","display_name":"Lung\u2010Hao Lee","orcid":"https://orcid.org/0000-0003-0472-7429"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Lung-Hao Lee","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084225297","display_name":"Yi L\u00fc","orcid":"https://orcid.org/0000-0002-0245-7392"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yi Lu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100763454","display_name":"Po\u2010Han Chen","orcid":"https://orcid.org/0000-0001-9760-9565"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Po-Han Chen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064835238","display_name":"Po\u2010Lei Lee","orcid":"https://orcid.org/0000-0002-3590-4507"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Po-Lei Lee","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5045326101","display_name":"Kuo\u2010Kai Shyu","orcid":"https://orcid.org/0000-0003-0505-5898"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kuo-Kai Shyu","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5078362082"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.3803,"has_fulltext":true,"cited_by_count":25,"citation_normalized_percentile":{"value":0.91446247,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"528","last_page":"532"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9983999729156494,"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":0.9943000078201294,"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/computer-science","display_name":"Computer science","score":0.8066364526748657},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7645024061203003},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.68679279088974},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.64149409532547},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6088489294052124},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.572138786315918},{"id":"https://openalex.org/keywords/biomedical-text-mining","display_name":"Biomedical text mining","score":0.5589305758476257},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5543802380561829},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5221350789070129},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5037958025932312},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.47235047817230225},{"id":"https://openalex.org/keywords/f1-score","display_name":"F1 score","score":0.43606850504875183},{"id":"https://openalex.org/keywords/natural-language-understanding","display_name":"Natural language understanding","score":0.42134159803390503},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.4184831380844116},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3810751438140869},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.29086560010910034},{"id":"https://openalex.org/keywords/text-mining","display_name":"Text mining","score":0.19068780541419983},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.07185515761375427}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8066364526748657},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7645024061203003},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.68679279088974},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.64149409532547},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6088489294052124},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.572138786315918},{"id":"https://openalex.org/C165141518","wikidata":"https://www.wikidata.org/wiki/Q4915126","display_name":"Biomedical text mining","level":3,"score":0.5589305758476257},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5543802380561829},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5221350789070129},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5037958025932312},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.47235047817230225},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.43606850504875183},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.42134159803390503},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.4184831380844116},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3810751438140869},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.29086560010910034},{"id":"https://openalex.org/C71472368","wikidata":"https://www.wikidata.org/wiki/Q676880","display_name":"Text mining","level":2,"score":0.19068780541419983},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.07185515761375427},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","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":"doi:10.18653/v1/w19-5058","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w19-5058","pdf_url":"https://www.aclweb.org/anthology/W19-5058.pdf","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 18th BioNLP Workshop and Shared Task","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/w19-5058","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w19-5058","pdf_url":"https://www.aclweb.org/anthology/W19-5058.pdf","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 18th BioNLP Workshop and Shared Task","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.8600000143051147,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2970872015.pdf","grobid_xml":"https://content.openalex.org/works/W2970872015.grobid-xml"},"referenced_works_count":9,"referenced_works":["https://openalex.org/W1840435438","https://openalex.org/W2143612262","https://openalex.org/W2470673105","https://openalex.org/W2608787653","https://openalex.org/W2888120268","https://openalex.org/W2896457183","https://openalex.org/W2963341956","https://openalex.org/W2963918774","https://openalex.org/W2970986790"],"related_works":["https://openalex.org/W4286233423","https://openalex.org/W3113264705","https://openalex.org/W2797817943","https://openalex.org/W4366770808","https://openalex.org/W4401129478","https://openalex.org/W3081652108","https://openalex.org/W4205149331","https://openalex.org/W4391229233","https://openalex.org/W4362508319","https://openalex.org/W4312858192"],"abstract_inverted_index":{"This":[0],"study":[1],"describes":[2],"the":[3,7,11,15,21,29,35,71,77],"model":[4],"design":[5],"of":[6,52,68],"NCUEE":[8],"system":[9],"for":[10,46],"MEDIQA":[12,62],"challenge":[13],"at":[14,61],"ACL-BioNLP":[16],"2019":[17],"workshop.":[18],"We":[19],"use":[20],"BERT":[22],"(Bidirectional":[23,37],"Encoder":[24],"Representations":[25],"from":[26],"Transformers)":[27],"as":[28],"word":[30],"embedding":[31],"method":[32],"to":[33],"integrate":[34],"BiLSTM":[36],"Long":[38],"Short-Term":[39],"Memory)":[40],"network":[41],"with":[42],"an":[43],"attention":[44],"mechanism":[45],"medical":[47],"text":[48],"inferences.":[49],"A":[50],"total":[51],"42":[53],"teams":[54],"participated":[55],"in":[56,76],"natural":[57],"language":[58],"inference":[59],"task":[60],"2019.":[63],"Our":[64],"best":[65],"accuracy":[66],"score":[67],"0.84":[69],"ranked":[70],"top-third":[72],"among":[73],"all":[74],"submissions":[75],"leaderboard.":[78]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
