{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T19:36:00Z","timestamp":1773862560741,"version":"3.50.1"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2020,2,24]],"date-time":"2020-02-24T00:00:00Z","timestamp":1582502400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,2,24]],"date-time":"2020-02-24T00:00:00Z","timestamp":1582502400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100007129","name":"Natural Science Foundation of Shandong Province","doi-asserted-by":"publisher","award":["ZR2016FQ07"],"award-info":[{"award-number":["ZR2016FQ07"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002338","name":"Ministry of Education of the People\u2019s Republic of China","doi-asserted-by":"publisher","award":["201602028031"],"award-info":[{"award-number":["201602028031"]}],"id":[{"id":"10.13039\/501100002338","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. & Cyber."],"published-print":{"date-parts":[[2020,9]]},"DOI":"10.1007\/s13042-020-01087-6","type":"journal-article","created":{"date-parts":[[2020,2,24]],"date-time":"2020-02-24T17:08:26Z","timestamp":1582564106000},"page":"1971-1979","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Fully-connected LSTM\u2013CRF on medical concept extraction"],"prefix":"10.1007","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2761-1867","authenticated-orcid":false,"given":"Jie","family":"Ji","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bairui","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongcheng","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,2,24]]},"reference":[{"issue":"5","key":"1087_CR1","doi-asserted-by":"publisher","first-page":"552","DOI":"10.1136\/amiajnl-2011-000203","volume":"18","author":"\u00d6 Uzuner","year":"2011","unstructured":"Uzuner \u00d6, South RB, Shen S, DuVall SL (2011) 2010 i2b2\/VA challenge on concepts, assertions, and relations in clinical text. J Am Med Inform Assoc 18(5):552\u2013556","journal-title":"J Am Med Inform Assoc"},{"issue":"3","key":"1087_CR2","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1007\/s13042-015-0426-6","volume":"9","author":"X Wang","year":"2018","unstructured":"Wang X, Yang C, Guan R (2018) A comparative study for biomedical named entity recognition. Int J Mach Learn Cybern 9(3):373\u2013382","journal-title":"Int J Mach Learn Cybern"},{"key":"1087_CR3","first-page":"72","volume":"9","author":"D Proux","year":"1998","unstructured":"Proux D, Rechenmann F, Julliard L, Pillet V, Jacq B (1998) Detecting gene symbols and names in biological texts. Genome Inform 9:72\u201380","journal-title":"Genome Inform"},{"issue":"1","key":"1087_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1472-6947-6-30","volume":"6","author":"QT Zeng","year":"2006","unstructured":"Zeng QT, Goryachev S, Weiss S, Sordo M, Murphy SN, Lazarus R (2006) Extracting principal diagnosis, co-morbidity and smoking status for asthma research: evaluation of a natural language processing system. BMC Med Inform Decis Mak 6(1):1\u201330","journal-title":"BMC Med Inform Decis Mak"},{"key":"1087_CR5","first-page":"156","volume":"2008","author":"JC Denny","year":"2008","unstructured":"Denny JC, Miller RA, Johnson KB, Spickard A III (2008) Development and evaluation of a clinical note section header terminology. AMIA Annu Symp Proc 2008:156","journal-title":"AMIA Annu Symp Proc"},{"key":"1087_CR6","first-page":"18","volume-title":"Ontology matching","author":"J Euzenat","year":"2007","unstructured":"Euzenat J, Shvaiko P (2007) Ontology matching. Springer, Heidelberg, p 18"},{"key":"1087_CR7","unstructured":"Horvitz EJ (2013) Reasoning about beliefs and actions under computational resource constraints. arXiv preprint arXiv:1304.2759"},{"key":"1087_CR8","unstructured":"Gaizauskas KHR, Demetriou G (2000) Term recognition and classification in biological science journal articles. In: Proceedings of the computational terminology for medical and biological applications workshop of the 2nd international conference on NLP, pp 37\u201344"},{"key":"1087_CR9","first-page":"517","volume":"2000","author":"TC Rindflesch","year":"1999","unstructured":"Rindflesch TC, Tanabe L, Weinstein JN, Hunter L (1999) EDGAR: extraction of drugs, genes and relations from the biomedical literature. Biocomputing 2000:517\u2013528","journal-title":"Biocomputing"},{"issue":"1","key":"1087_CR10","doi-asserted-by":"publisher","first-page":"S9","DOI":"10.1186\/1472-6947-15-S1-S9","volume":"15","author":"M Song","year":"2015","unstructured":"Song M, Yu H, Han WS (2015) Developing a hybrid dictionary-based bio-entity recognition technique. BMC Med Inform Decis Mak 15(1):S9","journal-title":"BMC Med Inform Decis Mak"},{"key":"1087_CR11","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1007\/11683568_8","volume-title":"International workshop on knowledge discovery in life science literature","author":"YC Wu","year":"2006","unstructured":"Wu YC, Fan TK, Lee YS, Yen SJ (2006) Extracting named entities using support vector machines. In: Bremer EG, Hakenberg J, Han EH, Berrar D, Dubitzky W (eds) International workshop on knowledge discovery in life science literature. Springer, Berlin, pp 91\u2013103"},{"key":"1087_CR12","unstructured":"Lafferty J, McCallum A, Pereira FC (2001) Conditional random fields: probabilistic models for segmenting and labeling sequence data. In: Proceedings of the 18th international conference on machine learning 2001, pp 282\u2013289"},{"key":"1087_CR13","doi-asserted-by":"crossref","unstructured":"Settles B (2004) Biomedical named entity recognition using conditional random fields and rich feature sets. In: Proceedings of the international joint workshop on natural language processing in biomedicine and its applications. Association for Computational Linguistics, pp 104\u2013107","DOI":"10.3115\/1567594.1567618"},{"key":"1087_CR14","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1007\/978-3-319-47674-2_15","volume-title":"Chinese computational linguistics and natural language processing based on naturally annotated big data","author":"L Li","year":"2016","unstructured":"Li L, Jin L, Jiang Y, Huang D (2016) Recognizing biomedical named entities based on the sentence vector\/twin word embeddings conditioned bidirectional LSTM. In: Sun M, Huang X, Lin H, Liu Z, Liu Y (eds) Chinese computational linguistics and natural language processing based on naturally annotated big data. Springer, Cham, pp 165\u2013176"},{"key":"1087_CR15","unstructured":"Boag W, Wacome K, Naumann T, Rumshisky A (2015) CliNER: a lightweight tool for clinical named entity recognition. In: AMIA joint summits on clinical research informatics (poster)"},{"key":"1087_CR16","doi-asserted-by":"crossref","unstructured":"Finkel J, Dingare S, Nguyen H, Nissim M, Manning C, Sinclair G (2004) Exploiting context for biomedical entity recognition: from syntax to the web. In: Proceedings of the international joint workshop on natural language processing in biomedicine and its applications. Association for Computational Linguistics, pp 88\u201391","DOI":"10.3115\/1567594.1567614"},{"issue":"1","key":"1087_CR17","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1016\/j.jbi.2011.10.007","volume":"45","author":"S Jonnalagadda","year":"2012","unstructured":"Jonnalagadda S, Cohen T, Wu S, Gonzalez G (2012) Enhancing clinical concept extraction with distributional semantics. J Biomed Inform 45(1):129\u2013140","journal-title":"J Biomed Inform"},{"key":"1087_CR18","unstructured":"Fu X, Ananiadou S (2014) Improving the extraction of clinical concepts from clinical records. In: Proceedings of BioTxtM14, pp 47\u201353"},{"issue":"1","key":"1087_CR19","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1016\/j.jbi.2011.10.007","volume":"45","author":"S Jonnalagadda","year":"2012","unstructured":"Jonnalagadda S, Cohen T, Wu S, Gonzalez G (2012) Enhancing clinical concept extraction with distributional semantics. J Biomed Inform 45(1):129\u2013140","journal-title":"J Biomed Inform"},{"key":"1087_CR20","unstructured":"Wu Y, Xu J, Jiang M, Zhang Y, Xu H (2015) A study of neural word embeddings for named entity recognition in clinical text. In: AMIA annual symposium proceedings. American Medical Informatics Association, vol 2015, p 1326"},{"issue":"5","key":"1087_CR21","doi-asserted-by":"publisher","first-page":"557","DOI":"10.1136\/amiajnl-2011-000150","volume":"18","author":"B de Bruijn","year":"2011","unstructured":"de Bruijn B, Cherry C, Kiritchenko S, Martin J, Zhu X (2011) Machine-learned solutions for three stages of clinical information extraction: the state of the art at i2b2 2010. J Am Med Inform Assoc 18(5):557\u2013562","journal-title":"J Am Med Inform Assoc"},{"issue":"Aug","key":"1087_CR22","first-page":"2493","volume":"12","author":"R Collobert","year":"2011","unstructured":"Collobert R, Weston J, Bottou L, Karlen M, Kavukcuoglu K, Kuksa P (2011) Natural language processing almost from scratch. J Mach Learn Res 12(Aug):2493\u20132537","journal-title":"J Mach Learn Res"},{"key":"1087_CR23","doi-asserted-by":"crossref","unstructured":"Barbieri F, Ballesteros M, Saggion H (2017) Are emojis predictable. arXiv preprint arXiv:1702.07285","DOI":"10.18653\/v1\/E17-2017"},{"key":"1087_CR24","unstructured":"Chalapathy R, Borzeshi EZ, Piccardi M (2016) Bidirectional LSTM\u2013CRF for clinical concept extraction. arXiv preprint arXiv:1611.08373"},{"issue":"14","key":"1087_CR25","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1093\/bioinformatics\/btx228","volume":"33","author":"M Habibi","year":"2017","unstructured":"Habibi M, Weber L, Neves M, Wiegandt DL, Leser U (2017) Deep learning with word embeddings improves biomedical named entity recognition. Bioinformatics 33(14):37\u201348","journal-title":"Bioinformatics"},{"key":"1087_CR26","unstructured":"Devlin J, Chang MW, Lee K et al (2018) BERT: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805"},{"key":"1087_CR27","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1016\/j.jpdc.2019.03.010","volume":"129","author":"Z Cui","year":"2019","unstructured":"Cui Z, Lei D, Wang P, Cai X, Zhang W (2019) Malicious code detection based on CNNs and multi-objective algorithm. J Parallel Distrib Comput 129:50\u201358","journal-title":"J Parallel Distrib Comput"},{"issue":"7","key":"1087_CR28","doi-asserted-by":"publisher","first-page":"3187","DOI":"10.1109\/TII.2018.2822680","volume":"14","author":"Z Cui","year":"2018","unstructured":"Cui Z, Xue F, Cai X, Cao Y, Wang G, Chen J (2018) Detection of malicious code variants based on deep learning. IEEE Trans Ind Inf 14(7):3187\u20133196","journal-title":"IEEE Trans Ind Inf"},{"key":"1087_CR29","doi-asserted-by":"crossref","unstructured":"Pennington J, Socher R, Manning C (2014) GloVe: global vectors for word representation. In: Proceedings of the 2014 conference on empirical methods in natural language processing, pp 1532\u20131543","DOI":"10.3115\/v1\/D14-1162"},{"key":"1087_CR30","unstructured":"Yin W, Kann K, Yu M, Schutze H (2017) Comparative study of CNN and RNN for natural language processing. arXiv preprint, arXiv:1702.01923"},{"key":"1087_CR31","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1613\/jair.4992","volume":"57","author":"Y Goldberg","year":"2016","unstructured":"Goldberg Y (2016) A primer on neural network models for natural language processing. J Artif Intell Res 57:345\u2013420","journal-title":"J Artif Intell Res"},{"key":"1087_CR32","unstructured":"Hermans M, Schrauwen B (2013) Training and analysing deep recurrent neural networks. In: Advances in neural information processing systems, pp 190\u2013198"},{"key":"1087_CR33","unstructured":"Pascanu R, Gulcehre C, Cho K, Bengio Y (2013) How to construct deep recurrent neural networks. arXiv preprint arXiv:1312.6026"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-020-01087-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s13042-020-01087-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-020-01087-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,2,23]],"date-time":"2021-02-23T00:31:26Z","timestamp":1614040286000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s13042-020-01087-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,2,24]]},"references-count":33,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2020,9]]}},"alternative-id":["1087"],"URL":"https:\/\/doi.org\/10.1007\/s13042-020-01087-6","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,2,24]]},"assertion":[{"value":"14 December 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 February 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 February 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}