{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T17:30:44Z","timestamp":1768411844237,"version":"3.49.0"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030389185","type":"print"},{"value":"9783030389192","type":"electronic"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-38919-2_31","type":"book-chapter","created":{"date-parts":[[2020,1,16]],"date-time":"2020-01-16T12:03:18Z","timestamp":1579176198000},"page":"375-387","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Towards the Named Entity Recognition Methods in Biomedical Field"],"prefix":"10.1007","author":[{"given":"Anna","family":"\u015aniegula","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7596-0813","authenticated-orcid":false,"given":"Aneta","family":"Poniszewska-Mara\u0144da","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"\u0141ukasz","family":"Chom\u0105tek","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,1,17]]},"reference":[{"key":"31_CR1","unstructured":"Abacha, A.B., Zweigenbaum, P.: Medical entity recognition: a comparison of semantic and statistical methods. In: Proceedings of BioNLP 2011 Workshop, BioNLP 2011, pp. 56\u201364 (2011)"},{"key":"31_CR2","unstructured":"Allahyari, M., et al.: A Brief Survey of Text Mining: Classifiation, Clustering and Extraction Techniques (2017)"},{"key":"31_CR3","unstructured":"Baevski, A., Edunov, S., Liu, Y., Zettlemoyer, L., Auli, M.: Cloze-driven Pretraining of Self-attention Networks. \nhttp:\/\/arxiv.org\/abs\/1903.07785"},{"key":"31_CR4","unstructured":"Boag, W., Sergeeva, E., Kulshreshtha, S., Szolovits, P., Rumshisky, A., Naumann, T.: CliNER 2.0: Accessible and Accurate Clinical Concept Extraction. \nhttp:\/\/arxiv.org\/abs\/1803.02245"},{"key":"31_CR5","doi-asserted-by":"crossref","unstructured":"Finkel, J.R., Grenager, T., Manning, C.: Incorporating non-local information into information extraction systems by Gibbs sampling. In: Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics, ACL 2005, pp. 363\u2013370 (2005)","DOI":"10.3115\/1219840.1219885"},{"issue":"Suppl. 1","key":"31_CR6","doi-asserted-by":"publisher","first-page":"S97","DOI":"10.1093\/bioinformatics\/17.suppl_1.S97","volume":"17","author":"V Hatzivassiloglou","year":"2001","unstructured":"Hatzivassiloglou, V., Dubou, P.A., Rzhetsky, A.: Disambiguating proteins, genes, and RNA in text: a machine learning approach. Bioinformatics 17(Suppl. 1), S97\u2013S106 (2001). ISSN 1367-4803","journal-title":"Bioinformatics"},{"issue":"8","key":"31_CR7","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9(8), 1735\u20131780 (1997). ISSN 0899-7667","journal-title":"Neural Comput."},{"key":"31_CR8","unstructured":"Jiang, R., Banchs, R.E., Li, H.: Evaluating and Combining Name Entity Recognition System, pp. 21\u201327. \nhttps:\/\/aclweb.org\/anthology\/papers\/W\/W16\/W16-2703\/"},{"key":"31_CR9","volume-title":"Speech and Language Processing, 2nd edin","author":"D Jurafsky","year":"2009","unstructured":"Jurafsky, D., Martin, J.H.: Speech and Language Processing, 2nd edin. Prentice Hall, Upper Saddle River (2009). ISBN 978-0-13-187321-6"},{"key":"31_CR10","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1055\/s-0038-1638592","volume":"17","author":"SM Meystre","year":"2008","unstructured":"Meystre, S.M., Savova, G.K., Kipper-Schuler, K.C., Hurdle, J.F.: Extracting information from textual documents in the electronic health record: a review of recent research. Yearb. Med. Inf. 17, 128\u2013144 (2008). ISSN 0943-4747","journal-title":"Yearb. Med. Inf."},{"issue":"1","key":"31_CR11","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1136\/amiajnl-2013-002544","volume":"22","author":"S Pradhan","year":"2014","unstructured":"Pradhan, S., et al.: Evaluating the state of the art in disorder recognition and normalization of the clinical narrative. J. Am. Med. Inf. Assoc. 22(1), 143\u2013154 (2014). ISSN 1527-974X","journal-title":"J. Am. Med. Inf. Assoc."},{"issue":"3","key":"31_CR12","doi-asserted-by":"publisher","first-page":"392","DOI":"10.1007\/s12204-018-1954-5","volume":"23","author":"Y Qin","year":"2018","unstructured":"Qin, Y., Zeng, Y.: Research of clinical named entity recognition based on Bi-LSTM-CRF. J. Shanghai Jiaotong Univ. (Sci.) 23(3), 392\u2013397 (2018)","journal-title":"J. Shanghai Jiaotong Univ. (Sci.)"},{"key":"31_CR13","doi-asserted-by":"crossref","unstructured":"Qiu, J., Wang, Q., Zhou, Y., Ruan, T., Gao, J.: Fast and accurate recognition of chinese clinical named entities with residual dilated convolutions. In: Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 935\u2013942 (2018)","DOI":"10.1109\/BIBM.2018.8621360"},{"key":"31_CR14","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1016\/j.procs.2016.09.123","volume":"100","author":"AP Quimbaya","year":"2016","unstructured":"Quimbaya, A.P., et al.: Named entity recognition over electronic health records through a combined dictionary-based approach. Procedia Comput. Sci. 100, 55\u201361 (2016)","journal-title":"Procedia Comput. Sci."},{"issue":"11","key":"31_CR15","doi-asserted-by":"publisher","first-page":"S5","DOI":"10.1186\/1471-2105-9-S11-S5","volume":"9","author":"Y Sasaki","year":"2008","unstructured":"Sasaki, Y., Tsuruoka, Y., McNaught, J., Ananiadou, S.: How to make the most of NE dictionaries in statistical NER. BMC Bioinform. 9(11), S5 (2008). ISSN 1471-2105","journal-title":"BMC Bioinform."},{"issue":"2","key":"31_CR16","doi-asserted-by":"publisher","first-page":"158","DOI":"10.1186\/s12938-018-0573-6","volume":"17","author":"Y-J Song","year":"2018","unstructured":"Song, Y.-J., Jo, B.-C., Park, C.-Y., Kim, J.-D., Kim, Y.-S.: Comparison of named entity recognition methodologies in biomedical documents. BioMed. Eng. OnLine 17(2), 158 (2018)","journal-title":"BioMed. Eng. OnLine"},{"key":"31_CR17","doi-asserted-by":"publisher","first-page":"4302425","DOI":"10.1155\/2018\/4302425","volume":"2018","author":"W Sun","year":"2018","unstructured":"Sun, W., Cai, Z., Li, Y., Liu, F., Fang, S., Wang, G.: Data processing and text mining technologies on electronic medical records: a review. J. Healthc. Eng. 2018, 4302425 (2018)","journal-title":"J. Healthc. Eng."},{"key":"31_CR18","unstructured":"Sutton, C., McCallum, A.: An Introduction to Conditional Random Fields. \narXiv:1011.4088\n\n [stat], November 2010"},{"key":"31_CR19","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1007\/978-3-319-93037-4_22","volume-title":"Advances in Knowledge Discovery and Data Mining","author":"J Zhang","year":"2018","unstructured":"Zhang, J., et al.: Category multi-representation: a unified solution for named entity recognition in clinical texts. In: Phung, D., Tseng, V.S., Webb, G.I., Ho, B., Ganji, M., Rashidi, L. (eds.) PAKDD 2018. LNCS (LNAI), vol. 10938, pp. 275\u2013287. Springer, Cham (2018). \nhttps:\/\/doi.org\/10.1007\/978-3-319-93037-4_22"}],"container-title":["Lecture Notes in Computer Science","SOFSEM 2020: Theory and Practice of Computer Science"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-38919-2_31","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,1,16]],"date-time":"2020-01-16T12:13:35Z","timestamp":1579176815000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-38919-2_31"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030389185","9783030389192"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-38919-2_31","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"17 January 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SOFSEM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Current Trends in Theory and Practice of Informatics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Limassol","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cyprus","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 January 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 January 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"46","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"sofsem2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/cyprusconferences.org\/sofsem2020\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"125","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"40","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"17","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"32% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.9","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.8","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}