{"id":"https://openalex.org/W4406518253","doi":"https://doi.org/10.1093/jamia/ocae326","title":"Semi-supervised learning from small annotated data and large unlabeled data for fine-grained Participants, Intervention, Comparison, and Outcomes entity recognition","display_name":"Semi-supervised learning from small annotated data and large unlabeled data for fine-grained Participants, Intervention, Comparison, and Outcomes entity recognition","publication_year":2025,"publication_date":"2025-01-17","ids":{"openalex":"https://openalex.org/W4406518253","doi":"https://doi.org/10.1093/jamia/ocae326","pmid":"https://pubmed.ncbi.nlm.nih.gov/39823371"},"language":"en","primary_location":{"id":"doi:10.1093/jamia/ocae326","is_oa":false,"landing_page_url":"https://doi.org/10.1093/jamia/ocae326","pdf_url":null,"source":{"id":"https://openalex.org/S129839026","display_name":"Journal of the American Medical Informatics Association","issn_l":"1067-5027","issn":["1067-5027","1527-974X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Medical Informatics Association","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11833487/","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084666933","display_name":"Fangyi Chen","orcid":"https://orcid.org/0000-0003-2926-1063"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Fangyi Chen","raw_affiliation_strings":["Department of Biomedical Informatics, Columbia University , New York, NY 10032,","Department of Biomedical Informatics, Columbia University, New York, NY 10032, United States"],"raw_orcid":"https://orcid.org/0000-0003-2926-1063","affiliations":[{"raw_affiliation_string":"Department of Biomedical Informatics, Columbia University , New York, NY 10032,","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Department of Biomedical Informatics, Columbia University, New York, NY 10032, United States","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005232556","display_name":"Gongbo Zhang","orcid":"https://orcid.org/0009-0001-0077-3615"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gongbo Zhang","raw_affiliation_strings":["Department of Biomedical Informatics, Columbia University , New York, NY 10032,","Department of Biomedical Informatics, Columbia University, New York, NY 10032, United States"],"raw_orcid":"https://orcid.org/0009-0001-0077-3615","affiliations":[{"raw_affiliation_string":"Department of Biomedical Informatics, Columbia University , New York, NY 10032,","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Department of Biomedical Informatics, Columbia University, New York, NY 10032, United States","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061866993","display_name":"Yilu Fang","orcid":"https://orcid.org/0000-0002-2681-1931"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yilu Fang","raw_affiliation_strings":["Department of Biomedical Informatics, Columbia University , New York, NY 10032,","Department of Biomedical Informatics, Columbia University, New York, NY 10032, United States"],"raw_orcid":"https://orcid.org/0000-0002-2681-1931","affiliations":[{"raw_affiliation_string":"Department of Biomedical Informatics, Columbia University , New York, NY 10032,","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Department of Biomedical Informatics, Columbia University, New York, NY 10032, United States","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085113833","display_name":"Yifan Peng","orcid":"https://orcid.org/0000-0001-9309-8331"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]},{"id":"https://openalex.org/I4387153466","display_name":"Weill Cornell Medicine","ror":"https://ror.org/02r109517","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295","https://openalex.org/I4387153466"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yifan Peng","raw_affiliation_strings":["Department of Population Health Sciences, Weill Cornell Medicine , New York, NY 10065,","Department of Population Health Sciences, Weill Cornell Medicine, New York, NY 10065, United States"],"raw_orcid":"https://orcid.org/0000-0001-9309-8331","affiliations":[{"raw_affiliation_string":"Department of Population Health Sciences, Weill Cornell Medicine , New York, NY 10065,","institution_ids":["https://openalex.org/I205783295","https://openalex.org/I4387153466"]},{"raw_affiliation_string":"Department of Population Health Sciences, Weill Cornell Medicine, New York, NY 10065, United States","institution_ids":["https://openalex.org/I205783295","https://openalex.org/I4387153466"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009604048","display_name":"Chunhua Weng","orcid":"https://orcid.org/0000-0002-9624-0214"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chunhua Weng","raw_affiliation_strings":["Department of Biomedical Informatics, Columbia University , New York, NY 10032,","Department of Biomedical Informatics, Columbia University, New York, NY 10032, United States"],"raw_orcid":"https://orcid.org/0000-0002-9624-0214","affiliations":[{"raw_affiliation_string":"Department of Biomedical Informatics, Columbia University , New York, NY 10032,","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Department of Biomedical Informatics, Columbia University, New York, NY 10032, United States","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5084666933"],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":{"value":3967,"currency":"USD","value_usd":3967},"apc_paid":null,"fwci":10.8419,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.97754687,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"32","issue":"3","first_page":"555","last_page":"565"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.4050000011920929,"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":0.4050000011920929,"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":0.28139999508857727,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.11810000240802765,"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/computer-science","display_name":"Computer science","score":0.6519220471382141},{"id":"https://openalex.org/keywords/intervention","display_name":"Intervention (counseling)","score":0.5611405968666077},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5371615886688232},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.382066011428833},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35703516006469727},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.22973597049713135},{"id":"https://openalex.org/keywords/nursing","display_name":"Nursing","score":0.0693340003490448}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6519220471382141},{"id":"https://openalex.org/C2780665704","wikidata":"https://www.wikidata.org/wiki/Q959298","display_name":"Intervention (counseling)","level":2,"score":0.5611405968666077},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5371615886688232},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.382066011428833},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35703516006469727},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.22973597049713135},{"id":"https://openalex.org/C159110408","wikidata":"https://www.wikidata.org/wiki/Q121176","display_name":"Nursing","level":1,"score":0.0693340003490448}],"mesh":[{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D002986","descriptor_name":"Clinical Trials as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002986","descriptor_name":"Clinical Trials as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002986","descriptor_name":"Clinical Trials as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D002986","descriptor_name":"Clinical Trials as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D002986","descriptor_name":"Clinical Trials as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D002986","descriptor_name":"Clinical Trials as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D002986","descriptor_name":"Clinical Trials as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002986","descriptor_name":"Clinical Trials as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D002986","descriptor_name":"Clinical Trials as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"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":"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":"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":"D009323","descriptor_name":"Natural Language Processing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009323","descriptor_name":"Natural Language Processing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009323","descriptor_name":"Natural Language Processing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009323","descriptor_name":"Natural Language Processing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009323","descriptor_name":"Natural Language Processing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009323","descriptor_name":"Natural Language Processing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009323","descriptor_name":"Natural Language Processing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009323","descriptor_name":"Natural Language Processing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009323","descriptor_name":"Natural Language Processing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016247","descriptor_name":"Information Storage and Retrieval","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D016247","descriptor_name":"Information Storage and Retrieval","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D016247","descriptor_name":"Information Storage and Retrieval","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D016247","descriptor_name":"Information Storage and Retrieval","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D016247","descriptor_name":"Information Storage and Retrieval","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D016247","descriptor_name":"Information Storage and Retrieval","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D066264","descriptor_name":"Datasets as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D066264","descriptor_name":"Datasets as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D066264","descriptor_name":"Datasets as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1093/jamia/ocae326","is_oa":false,"landing_page_url":"https://doi.org/10.1093/jamia/ocae326","pdf_url":null,"source":{"id":"https://openalex.org/S129839026","display_name":"Journal of the American Medical Informatics Association","issn_l":"1067-5027","issn":["1067-5027","1527-974X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Medical Informatics Association","raw_type":"journal-article"},{"id":"pmid:39823371","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39823371","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":"Journal of the American Medical Informatics Association : JAMIA","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11833487","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11833487/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Am Med Inform Assoc","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:11833487","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11833487/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Am Med Inform Assoc","raw_type":"Text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1584075922","display_name":null,"funder_award_id":"UL1TR001873","funder_id":"https://openalex.org/F4320337472","funder_display_name":"National Center for Advancing Translational Sciences"},{"id":"https://openalex.org/G4713501941","display_name":null,"funder_award_id":"R01LM014344","funder_id":"https://openalex.org/F4320337372","funder_display_name":"U.S. National Library of Medicine"},{"id":"https://openalex.org/G6325692374","display_name":null,"funder_award_id":"UL1TR002384","funder_id":"https://openalex.org/F4320337472","funder_display_name":"National Center for Advancing Translational Sciences"},{"id":"https://openalex.org/G682085659","display_name":null,"funder_award_id":"R01LM009886","funder_id":"https://openalex.org/F4320337372","funder_display_name":"U.S. National Library of Medicine"},{"id":"https://openalex.org/G7552868180","display_name":null,"funder_award_id":"R01HG012655","funder_id":"https://openalex.org/F4320337348","funder_display_name":"National Human Genome Research Institute"},{"id":"https://openalex.org/G7888995200","display_name":null,"funder_award_id":"R01LM014573","funder_id":"https://openalex.org/F4320337372","funder_display_name":"U.S. National Library of Medicine"},{"id":"https://openalex.org/G8763244384","display_name":null,"funder_award_id":"T15LM007079","funder_id":"https://openalex.org/F4320337372","funder_display_name":"U.S. National Library of Medicine"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337348","display_name":"National Human Genome Research Institute","ror":"https://ror.org/00baak391"},{"id":"https://openalex.org/F4320337372","display_name":"U.S. National Library of Medicine","ror":"https://ror.org/0060t0j89"},{"id":"https://openalex.org/F4320337472","display_name":"National Center for Advancing Translational Sciences","ror":"https://ror.org/04pw6fb54"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W586034241","https://openalex.org/W1914973955","https://openalex.org/W2022645200","https://openalex.org/W2027624580","https://openalex.org/W2036246082","https://openalex.org/W2037104885","https://openalex.org/W2064119490","https://openalex.org/W2079735306","https://openalex.org/W2097110957","https://openalex.org/W2104329117","https://openalex.org/W2108233388","https://openalex.org/W2114718442","https://openalex.org/W2118922351","https://openalex.org/W2131343135","https://openalex.org/W2134568263","https://openalex.org/W2146668368","https://openalex.org/W2555930919","https://openalex.org/W2593758073","https://openalex.org/W2795387844","https://openalex.org/W2902726914","https://openalex.org/W2911489562","https://openalex.org/W2962369866","https://openalex.org/W2963956526","https://openalex.org/W2992824360","https://openalex.org/W3016407396","https://openalex.org/W3046375318","https://openalex.org/W3190588453","https://openalex.org/W4281293036","https://openalex.org/W4283079132","https://openalex.org/W4287322212","https://openalex.org/W4315754517","https://openalex.org/W4377820139","https://openalex.org/W4386136017","https://openalex.org/W4386284317","https://openalex.org/W4386462961","https://openalex.org/W4386741020","https://openalex.org/W4386848061","https://openalex.org/W4391292768","https://openalex.org/W4392686512","https://openalex.org/W4394688596","https://openalex.org/W6617210626","https://openalex.org/W6639892535","https://openalex.org/W6675692969","https://openalex.org/W6677238145","https://openalex.org/W6749396741","https://openalex.org/W6765939562","https://openalex.org/W6781031682"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"OBJECTIVE:":[0],"Extracting":[1],"PICO":[2,28,43,58,84,204,229,252,291],"elements-Participants,":[3],"Intervention,":[4],"Comparison,":[5],"and":[6,18,86,105,117,136,155,170,206,233,266,276],"Outcomes-from":[7],"clinical":[8,14],"trial":[9],"literature":[10],"is":[11],"essential":[12],"for":[13,289],"evidence":[15],"retrieval,":[16],"appraisal,":[17],"synthesis.":[19],"Existing":[20],"approaches":[21],"do":[22],"not":[23],"distinguish":[24],"the":[25,71,94,114,123,132,138,151,156,163,188,213,242],"attributes":[26],"of":[27,54,73,83,125,165,177,184,244],"entities.":[29],"This":[30,271],"study":[31,272],"aims":[32],"to":[33,41,69,201,207,226,250,263],"develop":[34],"a":[35,52,66,74,100,106,181,202,274],"named":[36],"entity":[37],"recognition":[38],"(NER)":[39],"model":[40,190,198],"extract":[42],"entities":[44,85,230,253],"with":[45,57,103,141,285],"fine":[46],"granularities.":[47],"MATERIALS":[48],"AND":[49],"METHODS:":[50],"Using":[51],"corpus":[53],"2511":[55],"abstracts":[56],"mentions":[59],"from":[60,231],"4":[61],"public":[62],"datasets,":[63],"we":[64,92,146],"developed":[65,224],"semi-supervised":[67,246,278],"method":[68,174],"facilitate":[70],"training":[72],"NER":[75],"model,":[76],"FinePICO,":[77],"by":[78,193],"combining":[79],"limited":[80],"annotated":[81,134,153,185,287],"data":[82,283,288],"abundant":[87],"unlabeled":[88,282],"data.":[89],"For":[90],"evaluation,":[91],"divided":[93],"entire":[95,139],"dataset":[96],"into":[97],"2":[98],"subsets:":[99],"smaller":[101,152],"group":[102,108],"annotations":[104],"larger":[107],"without":[109],"annotations.":[110],"We":[111,161,223],"then":[112],"established":[113],"theoretical":[115],"lower":[116],"upper":[118],"performance":[119,124,164,236],"bounds":[120],"based":[121],"on":[122,131,137,149,259],"supervised":[126],"learning":[127,247],"models":[128],"trained":[129],"solely":[130],"small,":[133,286],"subset":[135,154],"set":[140,183],"complete":[142],"annotations,":[143],"respectively.":[144],"Finally,":[145],"evaluated":[147],"FinePICO":[148,166,225],"both":[150],"larger,":[157],"initially":[158],"unannotated":[159],"subset.":[160],"measured":[162],"using":[167,180,245],"precision,":[168],"recall,":[169],"F1.":[171],"RESULTS:":[172],"Our":[173],"achieved":[175],"precision/recall/F1":[176],"0.567/0.636/0.60,":[178],"respectively,":[179],"small":[182],"samples,":[186],"outperforming":[187],"baseline":[189],"(F1:":[191],"0.437)":[192],"more":[194],"than":[195],"16%.":[196],"The":[197],"demonstrates":[199],"generalizability":[200],"different":[203],"framework":[205],"another":[208],"corpus,":[209],"which":[210],"consistently":[211],"outperforms":[212],"benchmark":[214],"in":[215],"diverse":[216,238],"experimental":[217,239],"settings":[218],"(P-value":[219],"<":[220],".001).":[221],"DISCUSSION:":[222],"recognize":[227],"fine-grained":[228,290],"text":[232],"validated":[234],"its":[235],"across":[237],"settings,":[240],"highlighting":[241],"feasibility":[243],"(SSL)":[248],"techniques":[249],"enhance":[251],"extraction.":[254,292],"Future":[255],"work":[256],"can":[257],"focus":[258],"optimizing":[260],"SSL":[261],"algorithms":[262],"improve":[264],"efficiency":[265],"reduce":[267],"computational":[268],"costs.":[269],"CONCLUSION:":[270],"contributes":[273],"generalizable":[275],"effective":[277],"approach":[279],"leveraging":[280],"large":[281],"together":[284]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4}],"updated_date":"2026-06-05T09:01:59.212387","created_date":"2025-10-10T00:00:00"}
