{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T06:27:52Z","timestamp":1774074472627,"version":"3.50.1"},"reference-count":24,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,3,15]],"date-time":"2021-03-15T00:00:00Z","timestamp":1615766400000},"content-version":"vor","delay-in-days":73,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100005089","name":"Beijing Municipal Natural Science Foundation","doi-asserted-by":"publisher","award":["4212026"],"award-info":[{"award-number":["4212026"]}],"id":[{"id":"10.13039\/501100005089","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61772075"],"award-info":[{"award-number":["61772075"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Complexity"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p>The web is being loaded daily with a huge volume of data, mainly unstructured textual data, which increases the need for information extraction and NLP systems significantly. Named\u2010entity recognition task is a key step towards efficiently understanding text data and saving time and effort. Being a widely used language globally, English is taking over most of the research conducted in this field, especially in the biomedical domain. Unlike other languages, Arabic suffers from lack of resources. This work presents a BERT\u2010based model to identify biomedical named entities in the Arabic text data (specifically disease and treatment named entities) that investigates the effectiveness of pretraining a monolingual BERT model with a small\u2010scale biomedical dataset on enhancing the model understanding of Arabic biomedical text. The model performance was compared with two state\u2010of\u2010the\u2010art models (namely, AraBERT and multilingual BERT cased), and it outperformed both models with 85% F1\u2010score.<\/jats:p>","DOI":"10.1155\/2021\/6633213","type":"journal-article","created":{"date-parts":[[2021,3,15]],"date-time":"2021-03-15T19:35:09Z","timestamp":1615836909000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":46,"title":["ABioNER: A BERT\u2010Based Model for Arabic Biomedical Named\u2010Entity Recognition"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0420-6511","authenticated-orcid":false,"given":"Nada","family":"Boudjellal","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0137-4069","authenticated-orcid":false,"given":"Huaping","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5863-8467","authenticated-orcid":false,"given":"Asif","family":"Khan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3576-8365","authenticated-orcid":false,"given":"Arshad","family":"Ahmad","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4952-8100","authenticated-orcid":false,"given":"Rashid","family":"Naseem","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianyun","family":"Shang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lin","family":"Dai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2021,3,15]]},"reference":[{"key":"e_1_2_10_1_2","doi-asserted-by":"publisher","DOI":"10.1155\/2020\/8893749"},{"key":"e_1_2_10_2_2","article-title":"A named entity recognition system applied to Arabic text in the medical domain","volume":"12","author":"Alanazi S.","year":"2015","journal-title":"International Journal of Computer Science Issues"},{"key":"e_1_2_10_3_2","doi-asserted-by":"publisher","DOI":"10.18517\/ijaseit.7.2.1810"},{"key":"e_1_2_10_4_2","doi-asserted-by":"publisher","DOI":"10.1017\/s1351324916000097"},{"key":"e_1_2_10_5_2","doi-asserted-by":"publisher","DOI":"10.3844\/jcssp.2012.1285.1293"},{"key":"e_1_2_10_6_2","volume-title":"Minimally-supervised Methods for Arabic Named Entity Recognition","author":"Althobaiti M.","year":"2016"},{"key":"e_1_2_10_7_2","doi-asserted-by":"publisher","DOI":"10.1093\/jamia\/ocz200"},{"key":"e_1_2_10_8_2","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-6-s1-s8"},{"key":"e_1_2_10_9_2","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bts183"},{"key":"e_1_2_10_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2013.08.004"},{"key":"e_1_2_10_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2016.09.009"},{"key":"e_1_2_10_12_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12920-017-0316-8"},{"key":"e_1_2_10_13_2","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btx761"},{"key":"e_1_2_10_14_2","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btx815"},{"key":"e_1_2_10_15_2","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bty449"},{"key":"e_1_2_10_16_2","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btz682"},{"key":"e_1_2_10_17_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12911-019-0981-y"},{"key":"e_1_2_10_18_2","unstructured":"DevlinJ. ChangM.-W. LeeK. andToutanovaK. BERT: pre-training of deep bidirectional transformers for language understanding 1 Proceedings of the NAACL HLT 2019 June 2019 Minneapolis MN USA 4171\u20134186."},{"key":"e_1_2_10_19_2","unstructured":"AntounW. BalyF. andHajjH. 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