{"id":"https://openalex.org/W4417056893","doi":"https://doi.org/10.1371/journal.pcbi.1013722","title":"A meta-contrastive learning approach for clinical drug-drug interaction extraction from biomedical literature","display_name":"A meta-contrastive learning approach for clinical drug-drug interaction extraction from biomedical literature","publication_year":2025,"publication_date":"2025-12-05","ids":{"openalex":"https://openalex.org/W4417056893","doi":"https://doi.org/10.1371/journal.pcbi.1013722","pmid":"https://pubmed.ncbi.nlm.nih.gov/41348931"},"language":"en","primary_location":{"id":"doi:10.1371/journal.pcbi.1013722","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pcbi.1013722","pdf_url":null,"source":{"id":"https://openalex.org/S86033158","display_name":"PLoS Computational Biology","issn_l":"1553-734X","issn":["1553-734X","1553-7358"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS Computational Biology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1371/journal.pcbi.1013722","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102576400","display_name":"Yaxun Jia","orcid":"https://orcid.org/0000-0001-5808-4997"},"institutions":[{"id":"https://openalex.org/I4210128175","display_name":"Shanghai East Hospital","ror":"https://ror.org/038xmzj21","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128175"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yaxun Jia","raw_affiliation_strings":["Department of Radiation Oncology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-5808-4997","affiliations":[{"raw_affiliation_string":"Department of Radiation Oncology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China","institution_ids":["https://openalex.org/I4210128175"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100566856","display_name":"Yuan Zhu","orcid":"https://orcid.org/0009-0003-0323-8188"},"institutions":[{"id":"https://openalex.org/I4210158717","display_name":"Criminal Investigation Police University of China","ror":"https://ror.org/04vnevw94","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210158717"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhu Yuan","raw_affiliation_strings":["Department of Information Management, The National Police University for Criminal Justice, Baoding, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Management, The National Police University for Criminal Justice, Baoding, China","institution_ids":["https://openalex.org/I4210158717"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055485126","display_name":"Li\u2019an Zhu","orcid":"https://orcid.org/0000-0001-9657-9341"},"institutions":[{"id":"https://openalex.org/I4210128175","display_name":"Shanghai East Hospital","ror":"https://ror.org/038xmzj21","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128175"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lian Zhu","raw_affiliation_strings":["Department of Radiation Oncology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiation Oncology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China","institution_ids":["https://openalex.org/I4210128175"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023608453","display_name":"Zuo\u2010Lin Xiang","orcid":"https://orcid.org/0000-0002-5725-842X"},"institutions":[{"id":"https://openalex.org/I4210128175","display_name":"Shanghai East Hospital","ror":"https://ror.org/038xmzj21","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128175"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zuo-lin Xiang","raw_affiliation_strings":["Department of Radiation Oncology, Shanghai East Hospital Ji'an Hospital, Jian, China","Department of Radiation Oncology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-5725-842X","affiliations":[{"raw_affiliation_string":"Department of Radiation Oncology, Shanghai East Hospital Ji'an Hospital, Jian, China","institution_ids":["https://openalex.org/I4210128175"]},{"raw_affiliation_string":"Department of Radiation Oncology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China","institution_ids":["https://openalex.org/I4210128175"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5023608453","https://openalex.org/A5055485126","https://openalex.org/A5100566856","https://openalex.org/A5102576400"],"corresponding_institution_ids":["https://openalex.org/I4210128175","https://openalex.org/I4210158717"],"apc_list":{"value":2655,"currency":"USD","value_usd":2655},"apc_paid":{"value":2655,"currency":"USD","value_usd":2655},"fwci":1.0666,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.80438116,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"21","issue":"12","first_page":"e1013722","last_page":"e1013722"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11943","display_name":"Pharmacovigilance and Adverse Drug Reactions","score":0.46389999985694885,"subfield":{"id":"https://openalex.org/subfields/3005","display_name":"Toxicology"},"field":{"id":"https://openalex.org/fields/30","display_name":"Pharmacology, Toxicology and Pharmaceutics"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11943","display_name":"Pharmacovigilance and Adverse Drug Reactions","score":0.46389999985694885,"subfield":{"id":"https://openalex.org/subfields/3005","display_name":"Toxicology"},"field":{"id":"https://openalex.org/fields/30","display_name":"Pharmacology, Toxicology and Pharmaceutics"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.36039999127388,"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/T10211","display_name":"Computational Drug Discovery Methods","score":0.06019999831914902,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/benchmark","display_name":"Benchmark (surveying)","score":0.6071000099182129},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5857999920845032},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5583000183105469},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5465999841690063},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.5040000081062317},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.5002999901771545},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.4133000075817108},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3982999920845032}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.784500002861023},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6442000269889832},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6071000099182129},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5857999920845032},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5727999806404114},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5583000183105469},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5465999841690063},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.5040000081062317},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5002999901771545},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.4133000075817108},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3982999920845032},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3930000066757202},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.38670000433921814},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3856000006198883},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.34220001101493835},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.32330000400543213},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.31220000982284546},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30000001192092896},{"id":"https://openalex.org/C2777466982","wikidata":"https://www.wikidata.org/wiki/Q5227287","display_name":"Data extraction","level":3,"score":0.2903999984264374},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.2847999930381775},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2581999897956848},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.25369998812675476},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.25099998712539673}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004347","descriptor_name":"Drug Interactions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004347","descriptor_name":"Drug Interactions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004347","descriptor_name":"Drug Interactions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004347","descriptor_name":"Drug Interactions","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":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","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":"D060735","descriptor_name":"Pharmacovigilance","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060735","descriptor_name":"Pharmacovigilance","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060735","descriptor_name":"Pharmacovigilance","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060735","descriptor_name":"Pharmacovigilance","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D064420","descriptor_name":"Drug-Related Side Effects and Adverse Reactions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D064420","descriptor_name":"Drug-Related Side Effects and Adverse Reactions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D064420","descriptor_name":"Drug-Related Side Effects and Adverse Reactions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D064420","descriptor_name":"Drug-Related Side Effects and Adverse Reactions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1371/journal.pcbi.1013722","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pcbi.1013722","pdf_url":null,"source":{"id":"https://openalex.org/S86033158","display_name":"PLoS Computational Biology","issn_l":"1553-734X","issn":["1553-734X","1553-7358"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS Computational Biology","raw_type":"journal-article"},{"id":"pmid:41348931","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41348931","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":"PLoS computational biology","raw_type":null},{"id":"pmh:oai:doaj.org/article:4bd9e7391eb649e8af1b59af3d84b6d4","is_oa":true,"landing_page_url":"https://doaj.org/article/4bd9e7391eb649e8af1b59af3d84b6d4","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"PLoS Computational Biology, Vol 21, Iss 12, p e1013722 (2025)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:12680327","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12680327/","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"PLoS Comput Biol","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1371/journal.pcbi.1013722","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pcbi.1013722","pdf_url":null,"source":{"id":"https://openalex.org/S86033158","display_name":"PLoS Computational Biology","issn_l":"1553-734X","issn":["1553-734X","1553-7358"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS Computational Biology","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8903197484","display_name":null,"funder_award_id":"82160591","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W2170189740","https://openalex.org/W2485374661","https://openalex.org/W2560748602","https://openalex.org/W2579132201","https://openalex.org/W2648802171","https://openalex.org/W2761525601","https://openalex.org/W2765742249","https://openalex.org/W2775773698","https://openalex.org/W2780858805","https://openalex.org/W2790602452","https://openalex.org/W2910406387","https://openalex.org/W2911489562","https://openalex.org/W2963078194","https://openalex.org/W2963621436","https://openalex.org/W2964026782","https://openalex.org/W2975881542","https://openalex.org/W2984684268","https://openalex.org/W3005476894","https://openalex.org/W3019826089","https://openalex.org/W3027982260","https://openalex.org/W3043102475","https://openalex.org/W3082318197","https://openalex.org/W3093844547","https://openalex.org/W3126807607","https://openalex.org/W3213998394","https://openalex.org/W4205690061","https://openalex.org/W4212906192","https://openalex.org/W4291298322","https://openalex.org/W4294487796","https://openalex.org/W4309728330","https://openalex.org/W4319083661","https://openalex.org/W4364368785","https://openalex.org/W4366828082","https://openalex.org/W4379053404","https://openalex.org/W4380356533","https://openalex.org/W4385753194","https://openalex.org/W4388845467","https://openalex.org/W4391614544","https://openalex.org/W4399645916","https://openalex.org/W4402770592","https://openalex.org/W4403141421","https://openalex.org/W4403547249","https://openalex.org/W4405336815","https://openalex.org/W4406234938","https://openalex.org/W4406820916","https://openalex.org/W4407373623","https://openalex.org/W4411054984","https://openalex.org/W4411623894"],"related_works":[],"abstract_inverted_index":{"Drug-drug":[0],"interactions":[1],"(DDIs)":[2],"are":[3],"a":[4,47,78,153],"significant":[5],"source":[6],"of":[7,120,135],"adverse":[8],"drug":[9],"events":[10],"and":[11,18,39,72,87,106,127,155,174,181],"pose":[12],"critical":[13],"challenges":[14],"to":[15,36,59],"patient":[16],"safety":[17],"clinical":[19,170],"decision-making.":[20],"Extracting":[21],"DDIs":[22],"from":[23,161],"biomedical":[24,95,162,175],"literature":[25],"plays":[26],"an":[27],"essential":[28],"role":[29],"in":[30,93,148],"pharmacovigilance,":[31],"yet":[32],"remains":[33],"difficult":[34],"due":[35],"data":[37,182],"sparsity":[38],"high":[40],"annotation":[41],"costs.":[42],"This":[43],"study":[44],"presents":[45],"BioMCL-DDI,":[46],"novel":[48],"few-shot":[49],"learning":[50,76],"framework":[51],"that":[52],"integrates":[53],"meta-learning":[54],"with":[55,164],"contrastive":[56,74],"embedding":[57],"strategies":[58],"enable":[60],"efficient":[61],"DDI":[62,112,159],"extraction":[63,160],"under":[64],"limited":[65],"supervision.":[66],"BioMCL-DDI":[67,99,151],"jointly":[68],"optimizes":[69],"prototype-based":[70],"classification":[71],"supervised":[73],"representation":[75],"within":[77],"unified":[79],"architecture.":[80],"The":[81,115],"model":[82,116,143],"captures":[83],"both":[84],"intra-class":[85],"compactness":[86],"inter-class":[88],"separability,":[89],"enhancing":[90],"its":[91],"generalization":[92],"sparse":[94],"settings.":[96],"We":[97],"evaluate":[98],"on":[100,122,125,129],"three":[101],"benchmark":[102],"datasets:":[103],"DDI-2013,":[104,123],"DrugBank,":[105,126],"the":[107,130],"more":[108],"recent":[109],"TAC":[110,136],"2018":[111],"Extraction":[113],"corpus.":[114],"achieves":[117],"F1":[118],"scores":[119],"87.80%":[121],"86.00%":[124],"74.85%/74.82%":[128],"two":[131],"official":[132],"test":[133],"sets":[134],"2018,":[137],"consistently":[138],"outperforming":[139],"competitive":[140],"baselines.":[141],"Our":[142],"significantly":[144],"outperforms":[145],"state-of-the-art":[146],"baselines":[147],"low-resource":[149],"scenarios.":[150],"provides":[152],"scalable":[154],"effective":[156],"solution":[157],"for":[158,167],"texts,":[163],"strong":[165],"potential":[166],"integration":[168],"into":[169],"decision":[171],"support":[172],"systems":[173],"knowledge":[176],"bases.":[177],"All":[178],"our":[179],"code":[180],"have":[183],"been":[184],"publicly":[185],"released":[186],"at:":[187],"https://github.com/Hero-Legend/BioMCL-DDI.":[188]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-12-05T00:00:00"}