{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,1,26]],"date-time":"2024-01-26T00:17:07Z","timestamp":1706228227911},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684567","type":"print"},{"value":"9781643684574","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T00:00:00Z","timestamp":1706140800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,1,25]]},"abstract":"<jats:p>Automatic extraction of relations between drugs\/chemicals and proteins from ever-growing biomedical literature is required to build up-to-date knowledge bases in biomedicine. To promote the development of automated methods, BioCreative-VII organized a shared task \u2013 the DrugProt track, to recognize drug-protein entity relations from PubMed abstracts. We participated in the shared task and leveraged deep learning-based transformer models pre-trained on biomedical data to build ensemble approaches to automatically extract drug-protein relation from biomedical literature. On the main corpora of 10,750 abstracts, our best system obtained an F1-score of 77.60% (ranked 4th among 30 participating teams), and on the large-scale corpus of 2.4M documents, our system achieved micro-averaged F1-score of 77.32% (ranked 2nd among 9 system submissions). This demonstrates the effectiveness of domain-specific transformer models and ensemble approaches for automatic relation extraction from biomedical literature.<\/jats:p>","DOI":"10.3233\/shti231043","type":"book-chapter","created":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T10:24:38Z","timestamp":1706178278000},"source":"Crossref","is-referenced-by-count":0,"title":["Extracting Drug-Protein Relation from Literature Using Ensembles of Biomedical Transformers"],"prefix":"10.3233","author":[{"given":"Avisha","family":"Das","sequence":"first","affiliation":[{"name":"School of Biomedical Informatics, University of Texas Health Science Center at Houston; Yale University; Melax Technologies, Houston"}]},{"given":"Zhao","family":"Li","sequence":"additional","affiliation":[{"name":"School of Biomedical Informatics, University of Texas Health Science Center at Houston; Yale University; Melax Technologies, Houston"}]},{"given":"Qiang","family":"Wei","sequence":"additional","affiliation":[{"name":"School of Biomedical Informatics, University of Texas Health Science Center at Houston; Yale University; Melax Technologies, Houston"}]},{"given":"Jianfu","family":"Li","sequence":"additional","affiliation":[{"name":"School of Biomedical Informatics, University of Texas Health Science Center at Houston; Yale University; Melax Technologies, Houston"}]},{"given":"Liang-chin","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Biomedical Informatics, University of Texas Health Science Center at Houston; Yale University; Melax Technologies, Houston"}]},{"given":"Yan","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Biomedical Informatics, University of Texas Health Science Center at Houston; Yale University; Melax Technologies, Houston"}]},{"given":"Rongbin","family":"Li","sequence":"additional","affiliation":[{"name":"School of Biomedical Informatics, University of Texas Health Science Center at Houston; Yale University; Melax Technologies, Houston"}]},{"given":"Wenjin Jim","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Biomedical Informatics, University of Texas Health Science Center at Houston; Yale University; Melax Technologies, Houston"}]},{"given":"Hua","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Biomedical Informatics, University of Texas Health Science Center at Houston; Yale University; Melax Technologies, Houston"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2023 \u2014 The Future Is Accessible"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI231043","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T10:24:40Z","timestamp":1706178280000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI231043"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,25]]},"ISBN":["9781643684567","9781643684574"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti231043","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,25]]}}}