{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:17:31Z","timestamp":1750220251992,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":23,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,9,24]],"date-time":"2021-09-24T00:00:00Z","timestamp":1632441600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,9,24]]},"DOI":"10.1145\/3490322.3490336","type":"proceedings-article","created":{"date-parts":[[2021,12,27]],"date-time":"2021-12-27T15:29:45Z","timestamp":1640618985000},"page":"86-91","source":"Crossref","is-referenced-by-count":5,"title":["Medical Named Entity Recognition Based on Multi Feature Fusion of BERT"],"prefix":"10.1145","author":[{"given":"Zhengmin","family":"Li","sequence":"first","affiliation":[{"name":"College of Computer Science&Technology, Qingdao University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongyan","family":"Yun","sequence":"additional","affiliation":[{"name":"College of Computer Science&Technology, Qingdao University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenbo","family":"Guo","sequence":"additional","affiliation":[{"name":"College of Computer Science&Technology, Qingdao University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianjun","family":"Qi","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xidian University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,12,27]]},"reference":[{"issue":"13","key":"e_1_3_2_1_1_1","first-page":"2078","article-title":"Development of Electronic Medical Records Management Trend[J]","volume":"15","author":"Huang Jian","year":"2009","journal-title":"Medical Recapitulate"},{"issue":"01","key":"e_1_3_2_1_2_1","first-page":"55","volume":"32","author":"Lin Li YUN","year":"2019","journal-title":"Journal of Qingdao University (Natural Science Edition)"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"crossref","unstructured":"Bikel D M Miller S Schwartz R etal Nymble:a high-performance learning name-finder[J]. Anlp 1998 4: 194\u223c201. Bikel D M Miller S Schwartz R et al. Nymble:a high-performance learning name-finder[J]. Anlp 1998 4:194\u223c201.","DOI":"10.3115\/974557.974586"},{"volume-title":"An algorithm that learns what's in a name[J]. Machine learning","year":"1999","author":"Bikel D M","key":"e_1_3_2_1_4_1"},{"issue":"20","key":"e_1_3_2_1_5_1","first-page":"3237","article-title":"Named entity recognition based on bidirectional long short-term memory combined with case report form[J]","volume":"22","author":"Yang H","year":"2018","journal-title":"Chinese Journal of Tissue Engineering Research"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00104"},{"volume-title":"Fast and accurate entity recognition with iterated dilated convolutions[J]. arXiv preprint arXiv:1702.02098","year":"2017","author":"Strubell E","key":"e_1_3_2_1_7_1"},{"volume-title":"Chinese clinical named entity recognition with radical-level feature and self-attention mechanism[J]. Journal of biomedical informatics","year":"2019","author":"Yin M","key":"e_1_3_2_1_8_1"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-53817-4_4"},{"volume-title":"Efficient estimation of word representations in vector space[J]. arXiv preprint arXiv:1301.3781","year":"2013","author":"Mikolov T","key":"e_1_3_2_1_10_1"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"crossref","unstructured":"Pennington J Socher R Manning C D. Glove: Global vectors for word representation[C]\/\/Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP). 2014: 1532-1543. Pennington J Socher R Manning C D. Glove: Global vectors for word representation[C]\/\/Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP). 2014: 1532-1543.","DOI":"10.3115\/v1\/D14-1162"},{"volume-title":"Lee K","year":"1810","author":"Devlin J","key":"e_1_3_2_1_12_1"},{"volume-title":"Deep contextualized word representations[J]. arXiv preprint arXiv:1802.05365","year":"2018","author":"Peters M E","key":"e_1_3_2_1_13_1"},{"volume-title":"Improving language understanding by generative pre-training[J]","year":"2018","author":"Radford A","key":"e_1_3_2_1_14_1"},{"volume-title":"Roberta: A robustly optimized bert pretraining approach[J]. arXiv preprint arXiv:1907.11692","year":"2019","author":"Liu Y","key":"e_1_3_2_1_15_1"},{"volume-title":"What does BERT learn about the structure of language?[C]\/\/ACL 2019-57th Annual Meeting of the Association for Computational Linguistics","year":"2019","author":"Jawahar G","key":"e_1_3_2_1_16_1"},{"volume-title":"Long short-term memory[J]. Neural computation","year":"1997","author":"Hochreiter S","key":"e_1_3_2_1_17_1"},{"volume-title":"Fast and accurate entity recognition with iterated dilated convolutions[J]. arXiv preprint arXiv:1702.02098","year":"2017","author":"Strubell E","key":"e_1_3_2_1_18_1"},{"volume-title":"Milan A","year":"2019","author":"Lin G","key":"e_1_3_2_1_19_1"},{"volume-title":"Attention is all you need[J]. arXiv preprint arXiv:1706.03762","year":"2017","author":"Vaswani A","key":"e_1_3_2_1_20_1"},{"volume-title":"Li X","year":"1911","author":"Yan H","key":"e_1_3_2_1_21_1"},{"volume-title":"Pereira F C N. Conditional random fields: Probabilistic models for segmenting and labeling sequence data[J]","year":"2001","author":"Lafferty J","key":"e_1_3_2_1_22_1"},{"volume-title":"Automatic de-identification of electronic medical records using token-level and character-level conditional random fields[J]. Journal of biomedical informatics","year":"2015","author":"Liu Z","key":"e_1_3_2_1_23_1"}],"event":{"name":"ICBDT 2021: 2021 4th International Conference on Big Data Technologies","acronym":"ICBDT 2021","location":"Zibo China"},"container-title":["2021 4th International Conference on Big Data Technologies"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3490322.3490336","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3490322.3490336","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:30:42Z","timestamp":1750188642000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3490322.3490336"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,24]]},"references-count":23,"alternative-id":["10.1145\/3490322.3490336","10.1145\/3490322"],"URL":"https:\/\/doi.org\/10.1145\/3490322.3490336","relation":{},"subject":[],"published":{"date-parts":[[2021,9,24]]}}}