{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T12:37:30Z","timestamp":1723034250129},"reference-count":66,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["71471178","71871232","71371194","71171201"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"State Key Program of National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["71431006","71631008"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"Major Project for National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["71790615","71991463"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Projects of International Cooperation and Exchanges NSFC","award":["71210003"]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities, China","doi-asserted-by":"publisher","award":["2011RWSK003"],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004602","name":"Program for New Century Excellent Talents in University, China","doi-asserted-by":"publisher","award":["NCET-13-0604"],"id":[{"id":"10.13039\/501100004602","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Future Generation Computer Systems"],"published-print":{"date-parts":[[2021,1]]},"DOI":"10.1016\/j.future.2020.08.022","type":"journal-article","created":{"date-parts":[[2020,8,24]],"date-time":"2020-08-24T15:26:10Z","timestamp":1598282770000},"page":"581-604","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":12,"special_numbering":"C","title":["Deep neural network-based recognition of entities in Chinese online medical inquiry texts"],"prefix":"10.1016","volume":"114","author":[{"given":"Xin","family":"Liu","sequence":"first","affiliation":[]},{"given":"Yanju","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Zongrun","family":"Wang","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.future.2020.08.022_b1","doi-asserted-by":"crossref","first-page":"416","DOI":"10.1016\/j.chb.2016.12.068","article-title":"Information overload, psychological ill-being, and behavioral intention to continue online healthcare information search","volume":"70","author":"Swar","year":"2017","journal-title":"Comput. Hum. Behav."},{"issue":"2","key":"10.1016\/j.future.2020.08.022_b2","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1377\/hlthaff.23.2.116","article-title":"Physicians\u2019 use of electronic medical records: barriers and solutions","volume":"23","author":"Miller","year":"2004","journal-title":"Health Aff."},{"issue":"5","key":"10.1016\/j.future.2020.08.022_b3","doi-asserted-by":"crossref","first-page":"1007","DOI":"10.1093\/jamia\/ocv180","article-title":"Extracting information from the text of electronic medical records to improve case detection: a systematic review","volume":"23","author":"Ford","year":"2016","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"5","key":"10.1016\/j.future.2020.08.022_b4","doi-asserted-by":"crossref","first-page":"922","DOI":"10.1136\/amiajnl-2012-001317","article-title":"Towards comprehensive syntactic and semantic annotations of the clinical narrative","volume":"20","author":"Albright","year":"2013","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"10.1016\/j.future.2020.08.022_b5","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijmedinf.2019.02.008","article-title":"A systematic review of natural language processing and text mining of symptoms from electronic patient-authored text data","author":"Dreisbach","year":"2019","journal-title":"Int. J. Med. Inform."},{"key":"10.1016\/j.future.2020.08.022_b6","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.jbi.2015.09.010","article-title":"A study of active learning methods for named entity recognition in clinical text","author":"Chen","year":"2015","journal-title":"J. Biomed. Inform."},{"issue":"12","key":"10.1016\/j.future.2020.08.022_b7","doi-asserted-by":"crossref","first-page":"1289","DOI":"10.1016\/j.jclinepi.2012.05.003","article-title":"The quality, breadth, and timeliness of content updating vary substantially for 10 online medical texts: an analytic survey","volume":"65","author":"Prorok","year":"2012","journal-title":"J. Clin. Epidemiol."},{"issue":"3","key":"10.1016\/j.future.2020.08.022_b8","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1109\/TASLP.2016.2635445","article-title":"Personalizing recurrent-neural-network-based language model by social network","volume":"25","author":"Lee","year":"2017","journal-title":"IEEE\/ACM Trans. Audio Speech Lang. Process."},{"issue":"1","key":"10.1016\/j.future.2020.08.022_b9","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1016\/j.jbi.2012.08.006","article-title":"Validating the semantics of a medical iconic language using ontological reasoning","volume":"46","author":"Lamy","year":"2013","journal-title":"J. Biomed. Inform."},{"issue":"5","key":"10.1016\/j.future.2020.08.022_b10","doi-asserted-by":"crossref","first-page":"958","DOI":"10.1109\/TMM.2007.900150","article-title":"Can high-level concepts fill the semantic gap in video retrieval? A case study with broadcast news","volume":"9","author":"Hauptmann","year":"2007","journal-title":"IEEE Trans. Multimed."},{"issue":"10","key":"10.1016\/j.future.2020.08.022_b11","doi-asserted-by":"crossref","first-page":"1769","DOI":"10.1109\/TASLP.2018.2837384","article-title":"Semantic structure and interpretability of word embeddings","volume":"26","author":"Senel","year":"2018","journal-title":"IEEE Trans. Audio Speech Lang. Process."},{"key":"10.1016\/j.future.2020.08.022_b12","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/j.ijmedinf.2017.11.006","article-title":"Tracking word semantic change in biomedical literature","author":"Yan","year":"2018","journal-title":"Int. J. Med. Inform."},{"key":"10.1016\/j.future.2020.08.022_b13","doi-asserted-by":"crossref","first-page":"759","DOI":"10.1093\/jamia\/ocz103","article-title":"Online health community experiences of sexual minority women with cancer","author":"Lee","year":"2019","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"Feb","key":"10.1016\/j.future.2020.08.022_b14","first-page":"1137","article-title":"A neural probabilistic language model","volume":"3","author":"Bengio","year":"2003","journal-title":"J. Mach. Learn. Res."},{"issue":"Aug","key":"10.1016\/j.future.2020.08.022_b15","first-page":"2493","article-title":"Natural language processing (almost) from scratch","volume":"12","author":"Collobert","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.future.2020.08.022_b16","article-title":"Piecewise latent variables for neural variational text processing","author":"Serban","year":"2016","journal-title":"Comput. Lang."},{"key":"10.1016\/j.future.2020.08.022_b17","series-title":"Eleventh Annual Conference of the International Speech Communication Association","article-title":"Recurrent neural network based language model","author":"Mikolov","year":"2010"},{"key":"10.1016\/j.future.2020.08.022_b18","series-title":"Efficient estimation of word representations in vector space","author":"Mikolov","year":"2013"},{"key":"10.1016\/j.future.2020.08.022_b19","series-title":"International Conference on Artificial Intelligence","article-title":"Joint learning of character and word embeddings","author":"Chen","year":"2015"},{"key":"10.1016\/j.future.2020.08.022_b20","series-title":"International Conference on Neural Information Processing","article-title":"Radical-enhanced chinese character embedding","author":"Sun","year":"2014"},{"key":"10.1016\/j.future.2020.08.022_b21","series-title":"Component-enhanced chinese character embeddings","author":"Li","year":"2015"},{"key":"10.1016\/j.future.2020.08.022_b22","doi-asserted-by":"crossref","unstructured":"J. Yu, X. Jian, H. Xin, Y. Song, Joint embeddings of chinese words, characters, and fine-grained subcharacter components, in: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017.","DOI":"10.18653\/v1\/D17-1027"},{"key":"10.1016\/j.future.2020.08.022_b23","series-title":"ICML","article-title":"Compositional morphology for word representations and language modelling","author":"Botha","year":"2014"},{"key":"10.1016\/j.future.2020.08.022_b24","series-title":"ECML-PKDD","article-title":"Knowledge powered deep learning for word embedding","author":"Bian","year":"2014"},{"issue":"8","key":"10.1016\/j.future.2020.08.022_b25","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","article-title":"Long short-term memory","volume":"9","author":"Hochreiter","year":"1997","journal-title":"Neural Comput."},{"key":"10.1016\/j.future.2020.08.022_b26","series-title":"Neural architectures for named entity recognition","author":"Lample","year":"2016"},{"key":"10.1016\/j.future.2020.08.022_b27","first-page":"1188","article-title":"Distributed representations of sentences and documents","volume":"4","author":"Le","year":"2014","journal-title":"Comput. Sci."},{"key":"10.1016\/j.future.2020.08.022_b28","doi-asserted-by":"crossref","unstructured":"X. Chen, . Xipeng\u00a0Qiu, C. Zhu, P. Liu, X. Huang, Long short-term memory neural networks for chinese word segmentation, in: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 2015.","DOI":"10.18653\/v1\/D15-1141"},{"key":"10.1016\/j.future.2020.08.022_b29","series-title":"The 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP)","article-title":"Classifying relations via long short term memory networks along shortest dependency paths","author":"Yan","year":"2015"},{"key":"10.1016\/j.future.2020.08.022_b30","series-title":"The 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP)","article-title":"Chinese semantic role labeling with bidirectional recurrent neural networks","author":"Wang","year":"2015"},{"issue":"2","key":"10.1016\/j.future.2020.08.022_b31","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1136\/jamia.1994.95236146","article-title":"A general natural-language text processor for clinical radiology","volume":"1","author":"Friedman","year":"1994","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"3","key":"10.1016\/j.future.2020.08.022_b32","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1136\/jamia.2009.002733","article-title":"An overview of MetaMap: historical perspective and recent advances","volume":"17","author":"Aronson","year":"2010","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"5","key":"10.1016\/j.future.2020.08.022_b33","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1136\/jamia.2009.001560","article-title":"Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications","volume":"17","author":"Savova","year":"2010","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"5","key":"10.1016\/j.future.2020.08.022_b34","doi-asserted-by":"crossref","first-page":"514","DOI":"10.1136\/jamia.2010.003947","article-title":"Extracting medication information from clinical text","volume":"17","author":"Uzuner","year":"2010","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"5","key":"10.1016\/j.future.2020.08.022_b35","doi-asserted-by":"crossref","first-page":"552","DOI":"10.1136\/amiajnl-2011-000203","article-title":"2010 i2b2\/VA challenge on concepts, assertions, and relations in clinical text","volume":"18","author":"\u00d6","year":"2011","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"5","key":"10.1016\/j.future.2020.08.022_b36","doi-asserted-by":"crossref","first-page":"806","DOI":"10.1136\/amiajnl-2013-001628","article-title":"Evaluating temporal relations in clinical text: 2012 i2b2 challenge","volume":"20","author":"Sun","year":"2013","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"5","key":"10.1016\/j.future.2020.08.022_b37","doi-asserted-by":"crossref","first-page":"532","DOI":"10.1136\/jamia.2010.003657","article-title":"Medication information extraction with linguistic pattern matching and semantic rules","volume":"17","author":"Spasi\u0107","year":"2010","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"5","key":"10.1016\/j.future.2020.08.022_b38","doi-asserted-by":"crossref","first-page":"849","DOI":"10.1136\/amiajnl-2012-001607","article-title":"An end-to-end system to identify temporal relation in discharge summaries: 2012 i2b2 challenge","volume":"20","author":"Xu","year":"2013","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"5","key":"10.1016\/j.future.2020.08.022_b39","doi-asserted-by":"crossref","first-page":"828","DOI":"10.1136\/amiajnl-2013-001635","article-title":"A hybrid system for temporal information extraction from clinical text","volume":"20","author":"Tang","year":"2013","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"5","key":"10.1016\/j.future.2020.08.022_b40","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1136\/jamia.2010.004028","article-title":"Textractor: a hybrid system for medications and reason for their prescription extraction from clinical text documents","volume":"17","author":"Meystre","year":"2010","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"5","key":"10.1016\/j.future.2020.08.022_b41","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1136\/jamia.2010.003939","article-title":"High accuracy information extraction of medication information from clinical notes: 2009 i2b2 medication extraction challenge","volume":"17","author":"Patrick","year":"2010","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"5","key":"10.1016\/j.future.2020.08.022_b42","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1136\/amiajnl-2011-000163","article-title":"A study of machine-learning-based approaches to extract clinical entities and their assertions from discharge summaries","volume":"18","author":"Jiang","year":"2011","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"1","key":"10.1016\/j.future.2020.08.022_b43","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.jbi.2011.10.007","article-title":"Enhancing clinical concept extraction with distributional semantics","volume":"45","author":"Jonnalagadda","year":"2012","journal-title":"J. Biomed. Inform."},{"issue":"5","key":"10.1016\/j.future.2020.08.022_b44","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1136\/amiajnl-2011-000150","article-title":"Machine-learned solutions for three stages of clinical information extraction: the state of the art at i2b2 2010","volume":"18","author":"De\u00a0Bruijn","year":"2011","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"5","key":"10.1016\/j.future.2020.08.022_b45","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1136\/amiajnl-2011-000164","article-title":"MITRE system for clinical assertion status classification","volume":"18","author":"Clark","year":"2011","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"8","key":"10.1016\/j.future.2020.08.022_b46","first-page":"1537","article-title":"An overview of research on electronic medical record oriented named entity recognition and entity relation extraction","volume":"40","author":"Yang","year":"2014","journal-title":"Acta Automat. Sinica"},{"issue":"2","key":"10.1016\/j.future.2020.08.022_b47","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1136\/jamia.2009.000893","article-title":"Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2)","volume":"17","author":"Murphy","year":"2010","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"11","key":"10.1016\/j.future.2020.08.022_b48","first-page":"2725","article-title":"Corpus construction for named entities and entity relations on Chinese electronic medical records","volume":"27","author":"Yang","year":"2016","journal-title":"J. Softw."},{"key":"10.1016\/j.future.2020.08.022_b49","unstructured":"L. Jianbo, T. Buzhou, L. Xueqin, G. Kaihua, J. Min, X. Hua, A comprehensive study of named entity recognition in chinese clinical text, J. Am. Med. Inform. Assoc. (5) (0) 808\u2013814."},{"issue":"1","key":"10.1016\/j.future.2020.08.022_b50","first-page":"1","article-title":"Entity recognition research in online medical texts","volume":"52","author":"Su","year":"2016","journal-title":"Acta Sci. Natur. Univ. Pekinensis"},{"key":"10.1016\/j.future.2020.08.022_b51","doi-asserted-by":"crossref","first-page":"112","DOI":"10.3389\/fncom.2017.00112","article-title":"Computational foundations of natural intelligence","volume":"11","author":"Marcel","year":"2017","journal-title":"Front. Comput. Neurosci."},{"key":"10.1016\/j.future.2020.08.022_b52","series-title":"Advances in Neural Information Processing Systems","first-page":"3111","article-title":"Distributed representations of words and phrases and their compositionality","author":"Mikolov","year":"2013"},{"issue":"2","key":"10.1016\/j.future.2020.08.022_b53","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1162\/coli.2007.33.2.161","article-title":"Dependency-based construction of semantic space models","volume":"33","author":"Pad\u00f3","year":"2007","journal-title":"Comput. Linguist."},{"key":"10.1016\/j.future.2020.08.022_b54","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1162\/tacl_a_00051","article-title":"Enriching word vectors with subword information","volume":"5","author":"Bojanowski","year":"2017","journal-title":"Trans. Assoc. Comput. Linguist."},{"key":"10.1016\/j.future.2020.08.022_b55","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/j.knosys.2016.05.045","article-title":"Learning distributed word representation with multi-contextual mixed embedding","volume":"106","author":"Li","year":"2016","journal-title":"Knowl.-Based Syst."},{"issue":"8","key":"10.1016\/j.future.2020.08.022_b56","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1016\/j.patrec.2009.09.011","article-title":"Data clustering: 50 years beyond K-means","volume":"31","author":"Jain","year":"2010","journal-title":"Pattern Recognit. Lett."},{"key":"10.1016\/j.future.2020.08.022_b57","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1016\/j.patrec.2017.03.008","article-title":"K-means clustering with outlier removal","volume":"90","author":"Gan","year":"2017","journal-title":"Pattern Recognit. Lett."},{"issue":"9","key":"10.1016\/j.future.2020.08.022_b58","doi-asserted-by":"crossref","first-page":"4509","DOI":"10.1109\/TIP.2017.2713099","article-title":"Deep convolutional neural network for inverse problems in imaging","volume":"26","author":"Jin","year":"2017","journal-title":"IEEE Trans. Image Process."},{"issue":"1","key":"10.1016\/j.future.2020.08.022_b59","first-page":"2287","article-title":"Stereo matching by training a convolutional neural network to compare image patches","volume":"17","author":"\u017dbontar","year":"2016","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.future.2020.08.022_b60","doi-asserted-by":"crossref","first-page":"806","DOI":"10.1016\/j.neucom.2015.09.096","article-title":"Semantic expansion using word embedding clustering and convolutional neural network for improving short text classification","volume":"174","author":"Wang","year":"2016","journal-title":"Neurocomputing"},{"key":"10.1016\/j.future.2020.08.022_b61","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.patrec.2016.06.012","article-title":"Representation learning for very short texts using weighted word embedding aggregation","volume":"80","author":"De\u00a0Boom","year":"2016","journal-title":"Pattern Recognit. Lett."},{"key":"10.1016\/j.future.2020.08.022_b62","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.jbi.2017.05.002","article-title":"Character-level neural network for biomedical named entity recognition","volume":"70","author":"Gridach","year":"2017","journal-title":"J. Biomed. Inform."},{"key":"10.1016\/j.future.2020.08.022_b63","series-title":"Improving named entity recognition for chinese social media with word segmentation representation learning","author":"Peng","year":"2016"},{"key":"10.1016\/j.future.2020.08.022_b64","article-title":"Neural machine translation by jointly learning to align and translate","volume":"2014","author":"Bahdanau","year":"2019","journal-title":"Comput. Sci."},{"key":"10.1016\/j.future.2020.08.022_b65","series-title":"IOP Conference Series: Earth and Environmental Science, Vol. 108","article-title":"Design and implementation of distributed crawler system based on scrapy","author":"Fan","year":"2018"},{"issue":"1","key":"10.1016\/j.future.2020.08.022_b66","first-page":"1929","article-title":"Dropout: a simple way to prevent neural networks from overfitting","volume":"15","author":"Srivastava","year":"2014","journal-title":"J. Mach. Learn. Res."}],"container-title":["Future Generation Computer Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0167739X20317453?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0167739X20317453?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2020,12,22]],"date-time":"2020-12-22T23:41:30Z","timestamp":1608680490000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0167739X20317453"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1]]},"references-count":66,"alternative-id":["S0167739X20317453"],"URL":"https:\/\/doi.org\/10.1016\/j.future.2020.08.022","relation":{},"ISSN":["0167-739X"],"issn-type":[{"value":"0167-739X","type":"print"}],"subject":[],"published":{"date-parts":[[2021,1]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Deep neural network-based recognition of entities in Chinese online medical inquiry texts","name":"articletitle","label":"Article Title"},{"value":"Future Generation Computer Systems","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.future.2020.08.022","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2020 Published by Elsevier B.V.","name":"copyright","label":"Copyright"}]}}
  NODES
Association 1
COMMUNITY 1
INTERN 4
Note 1
Project 2