{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T15:14:43Z","timestamp":1783696483381,"version":"3.55.0"},"reference-count":63,"publisher":"Elsevier BV","issue":"7","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Information Processing & Management"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.ipm.2026.104784","type":"journal-article","created":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T00:38:12Z","timestamp":1777336692000},"page":"104784","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PB","title":["A hierarchical RL model for Chinese medical NER with radical semantics and dynamic decision"],"prefix":"10.1016","volume":"63","author":[{"given":"Guangce","family":"Ruan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Xia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ipm.2026.104784_bib0001","unstructured":"Ashok, D., & Lipton, Z. C. (2023). PromptNER: Prompting for named entity recognition. 10.48550\/arXiv.2305.15444."},{"key":"10.1016\/j.ipm.2026.104784_bib0002","series-title":"Machine learning and knowledge discovery in databases: Applied data science track","article-title":"DistALANER: Distantly supervised active learning augmented named entity recognition in the open source software ecosystem","volume":"vol. 14950","author":"Banerjee","year":"2024"},{"key":"10.1016\/j.ipm.2026.104784_bib0003","series-title":"Proceedings of the 2024 joint international conference on computational linguistics, language resources and evaluation (LREC-COLING 2024)","first-page":"7220","article-title":"Few-shot named entity recognition via superposition concept discrimination","author":"Chen","year":"2024"},{"issue":"8","key":"10.1016\/j.ipm.2026.104784_bib0004","first-page":"1680","article-title":"Named entity recognition for Chinese electronic medical record based on BERT-BiGRU-CRF and attention mechanism","volume":"44","author":"Chen","year":"2023","journal-title":"Journal of Chinese Computer Systems"},{"key":"10.1016\/j.ipm.2026.104784_bib0005","unstructured":"Chiang, W. L., Li, Z., Lin, Z., Sheng, Y., Wu, Z., Zhang, H., Zheng, L., Zhuang, S., Zhuang, Y., Gonzalez, J. E., Stoica, I., & Xing, E. P. (2023). Vicuna: An open-source chatbot impressing GPT-4 with 90% ChatGPT quality. LMSys Blog. https:\/\/lmsys.org\/blog\/2023-03-30-vicuna\/."},{"key":"10.1016\/j.ipm.2026.104784_bib0006","series-title":"Proceedings of the seventh conference on natural language learning at HLT-NAACL 2003","first-page":"160","article-title":"Named entity recognition with a maximum entropy approach","author":"Chieu","year":"2003"},{"key":"10.1016\/j.ipm.2026.104784_bib0007","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1162\/tacl_a_00104","article-title":"Named entity recognition with bidirectional LSTM-CNNs","volume":"4","author":"Chiu","year":"2016","journal-title":"Transactions of the Association for Computational Linguistics"},{"key":"10.1016\/j.ipm.2026.104784_bib0008","series-title":"Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP)","first-page":"1724","article-title":"Learning phrase representations using RNN encoder-decoder for statistical machine translation","author":"Cho","year":"2014"},{"issue":"1","key":"10.1016\/j.ipm.2026.104784_bib0009","first-page":"2493","article-title":"Natural language processing (almost) from scratch","volume":"12","author":"Collobert","year":"2011","journal-title":"Journal of Machine Learning Research"},{"key":"10.1016\/j.ipm.2026.104784_bib0010","first-page":"1","article-title":"Chinese medical named entity recognition integrating multi-level granular features","author":"Dai","year":"2025","journal-title":"Computer Engineering"},{"key":"10.1016\/j.ipm.2026.104784_bib0011","series-title":"Course in general linguistics","author":"de Saussure","year":"1916"},{"key":"10.1016\/j.ipm.2026.104784_bib0012","series-title":"Proceedings of the 63rd annual meeting of the association for computational linguistics, volume 1: Long papers","first-page":"26813","article-title":"Automated structured radiology report generation","author":"Delbrouck","year":"2025"},{"key":"10.1016\/j.ipm.2026.104784_bib0013","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.jbi.2013.12.006","article-title":"NCBI disease corpus: A resource for disease name recognition and concept normalization","volume":"47","author":"Do\u011fan","year":"2014","journal-title":"Journal of Biomedical Informatics"},{"key":"10.1016\/j.ipm.2026.104784_bib0014","doi-asserted-by":"crossref","unstructured":"Du, X., Zhao, H., Xing, D., Jia, Y., & Zan, H. (2024a). MRC-based nested medical NER with co-prediction and adaptive pre-training. http:\/\/arxiv.org\/pdf\/2403.15800v1.","DOI":"10.63317\/3zcu3okziosa"},{"key":"10.1016\/j.ipm.2026.104784_bib0015","series-title":"Proceedings of the 2024 joint international conference on computational linguistics, language resources and evaluation (LREC-COLING 2024)","first-page":"11669","article-title":"MRC-based nested medical NER with co-prediction and adaptive pre-training","author":"Du","year":"2024"},{"issue":"2","key":"10.1016\/j.ipm.2026.104784_bib0016","first-page":"26","article-title":"Analysis of neural network modules for named entity recognition of Chinese medical texts","volume":"7","author":"Duan","year":"2023","journal-title":"Data Analysis and Knowledge Discovery"},{"issue":"1","key":"10.1016\/j.ipm.2026.104784_bib0017","first-page":"144","article-title":"Chinese medical named entity recognition based on RoBERTa and adversarial training","volume":"49","author":"Guo","year":"2023","journal-title":"Journal of East China University of Science and Technology (Natural Science Edition)"},{"issue":"8","key":"10.1016\/j.ipm.2026.104784_bib0018","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 Computation"},{"key":"10.1016\/j.ipm.2026.104784_bib0019","unstructured":"Huang, Z., Xu, W., & Yu, K. (2015). Bidirectional LSTM-CRF models for sequence tagging. https:\/\/arxiv.org\/abs\/1508.01991v1."},{"issue":"2","key":"10.1016\/j.ipm.2026.104784_bib0020","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1037\/0033-295X.95.2.163","article-title":"The role of knowledge in discourse comprehension: A construction-integration model","volume":"95","author":"Kintsch","year":"1988","journal-title":"Psychological Review"},{"key":"10.1016\/j.ipm.2026.104784_bib0021","series-title":"Proceedings of the 18th international conference on machine learning","first-page":"282","article-title":"Conditional random fields: Probabilistic models for segmenting and labeling sequence data","author":"Lafferty","year":"2001"},{"key":"10.1016\/j.ipm.2026.104784_bib0022","series-title":"Advances in neural information processing systems","first-page":"78824","article-title":"CQM: Curriculum reinforcement learning with a quantized world model","volume":"vol. 36","author":"Lee","year":"2023"},{"issue":"8","key":"10.1016\/j.ipm.2026.104784_bib0023","first-page":"3032","article-title":"Chinese medical named entity recognition combined with multi-feature embedding and multi-network fusion","volume":"45","author":"Lei","year":"2023","journal-title":"Journal of Electronics & Information Technology"},{"key":"10.1016\/j.ipm.2026.104784_bib0024","doi-asserted-by":"crossref","first-page":"2123","DOI":"10.1109\/TASLP.2021.3086978","article-title":"A multi-agent communication based model for nested named entity recognition","volume":"29","author":"Li","year":"2021","journal-title":"IEEE\/ACM Transactions on Audio, Speech, and Language Processing"},{"issue":"1","key":"10.1016\/j.ipm.2026.104784_bib0025","first-page":"102","article-title":"BERT-IDCNN-CRF for named entity recognition in chinese","volume":"55","author":"Li","year":"2020","journal-title":"Journal of Shandong University (Natural Science)"},{"issue":"1","key":"10.1016\/j.ipm.2026.104784_bib0026","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2023.103541","article-title":"EPIC: An epidemiological investigation of COVID-19 dataset for Chinese named entity recognition","volume":"61","author":"Li","year":"2024","journal-title":"Information Processing & Management"},{"issue":"3","key":"10.1016\/j.ipm.2026.104784_bib0027","first-page":"117","article-title":"Academic nested entity recognition based on unified processing strategy","volume":"9","author":"Li","year":"2025","journal-title":"Data Analysis and Knowledge Discovery"},{"issue":"4","key":"10.1016\/j.ipm.2026.104784_bib0028","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2025.104148","article-title":"Quality-controllable automatic construction method of Chinese knowledge graph for medical decision-making applications","volume":"62","author":"Li","year":"2025","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2026.104784_bib0029","series-title":"Proceedings of the ninth international workshop on health text mining and information analysis","first-page":"165","article-title":"Self-training improves recurrent neural networks performance for temporal relation extraction","author":"Lin","year":"2018"},{"issue":"3","key":"10.1016\/j.ipm.2026.104784_bib0030","first-page":"327","article-title":"Automatic labeling and extraction of terms in natural language processing for acupuncture clinical literature","volume":"42","author":"Liu","year":"2022","journal-title":"Chinese Acupuncture & Moxibustion"},{"issue":"2","key":"10.1016\/j.ipm.2026.104784_bib0031","first-page":"337","article-title":"Chinese medical named entity recognition based on multi-granularity glyph enhancement","volume":"50","author":"Liu","year":"2024","journal-title":"Computer Engineering"},{"issue":"2","key":"10.1016\/j.ipm.2026.104784_bib0032","first-page":"330","article-title":"Named entity recognition of Chinese electronic health records incorporating phonetic and part-of-speech features","volume":"46","author":"Lu","year":"2025","journal-title":"Journal of Chinese Computer Systems"},{"issue":"10","key":"10.1016\/j.ipm.2026.104784_bib0033","first-page":"1943","article-title":"Chinese clinical named entity recognition based on stroke ELMo and multi-task learning","volume":"43","author":"Luo","year":"2020","journal-title":"Chinese Journal of Computers"},{"key":"10.1016\/j.ipm.2026.104784_bib0034","series-title":"2024 International joint conference on neural networks (IJCNN)","first-page":"1","article-title":"Multi-granularity dual-aware contrastive learning for few-shot named entity recognition","author":"Ma","year":"2024"},{"key":"10.1016\/j.ipm.2026.104784_bib0035","series-title":"European conference on machine learning","first-page":"648","article-title":"Sequence labeling with reinforcement learning and ranking algorithms","author":"Maes","year":"2007"},{"issue":"2","key":"10.1016\/j.ipm.2026.104784_bib0036","first-page":"260","article-title":"Chinese medical named entity recognition based on soft-lexicon and adversarial training","volume":"47","author":"Pan","year":"2024","journal-title":"Journal of Shanxi University (Natural Science Edition)"},{"issue":"9","key":"10.1016\/j.ipm.2026.104784_bib0037","first-page":"3117","article-title":"JURIS: Judical understanding-enhanced reasoning via instruction-tuned strategies for named entity recognition","volume":"53","author":"Peng","year":"2025","journal-title":"Acta Electronica Sinica"},{"key":"10.1016\/j.ipm.2026.104784_bib0038","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.procs.2016.09.123","article-title":"Named entity recognition over electronic health records through a combined dictionary-based approach","volume":"100","author":"Quimbaya","year":"2016","journal-title":"Procedia Computer Science"},{"issue":"7","key":"10.1016\/j.ipm.2026.104784_bib0039","first-page":"890","article-title":"Diabetes named entity recognition based on feature fusion","volume":"41","author":"Ren","year":"2024","journal-title":"Chinese Journal of Medical Physics"},{"issue":"2","key":"10.1016\/j.ipm.2026.104784_bib0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2021.102841","article-title":"An entity recognition model based on deep learning fusion of text feature","volume":"59","author":"Shang","year":"2022","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2026.104784_bib0041","series-title":"Proceedings of the 2020 conference on empirical methods in natural language processing (EMNLP)","first-page":"4700","article-title":"BioMegatron: Larger biomedical domain language model","author":"Shin","year":"2020"},{"key":"10.1016\/j.ipm.2026.104784_bib0042","series-title":"Advances in neural information processing systems","first-page":"1057","article-title":"Policy gradient methods for reinforcement learning with function approximation","volume":"vol. 12","author":"Sutton","year":"1999"},{"key":"10.1016\/j.ipm.2026.104784_bib0043","series-title":"Proceedings of the AAAI conference on artificial intelligence","first-page":"7072","article-title":"A hierarchical framework for relation extraction with reinforcement learning","volume":"vol. 33","author":"Takanobu","year":"2019"},{"key":"10.1016\/j.ipm.2026.104784_bib0044","series-title":"Proceedings of the 6th conference on natural language learning (coNLL-2002)","first-page":"119","article-title":"Use of support vector machines in extended named entity recognition","author":"Takeuchi","year":"2002"},{"key":"10.1016\/j.ipm.2026.104784_bib0045","series-title":"Natural language processing and Chinese computing","first-page":"357","article-title":"Reinforcement learning for named entity recognition from noisy data","volume":"vol. 12430","author":"Wan","year":"2020"},{"issue":"6","key":"10.1016\/j.ipm.2026.104784_bib0046","doi-asserted-by":"crossref","first-page":"10504","DOI":"10.1109\/TNNLS.2025.3528416","article-title":"Hierarchical label-enhanced contrastive learning for Chinese NER","volume":"36","author":"Wang","year":"2025","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"7","key":"10.1016\/j.ipm.2026.104784_bib0047","first-page":"324","article-title":"Chinese medical entity recognition based on attention enhancement and feature fusion","volume":"50","author":"Wang","year":"2024","journal-title":"Computer Engineering"},{"key":"10.1016\/j.ipm.2026.104784_bib0048","series-title":"Proceedings of the ACM web conference 2025","first-page":"4183","article-title":"A cooperative multi-agent framework for zero-shot named entity recognition","author":"Wang","year":"2025"},{"issue":"2","key":"10.1016\/j.ipm.2026.104784_bib0049","first-page":"150","article-title":"A Chinese toponym recognition method based on conditional random field","volume":"42","author":"Wu","year":"2017","journal-title":"Geomatics and Information Science of Wuhan University"},{"issue":"1","key":"10.1016\/j.ipm.2026.104784_bib0050","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2024.103902","article-title":"DualFLAT: Dual flat-lattice transformer for domain-specific Chinese named entity recognition","volume":"62","author":"Xiao","year":"2024","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2026.104784_bib0051","unstructured":"Xiong, H., Wang, S., Zhu, Y., Zhao, Z., Liu, Y., Huang, L., Wang, Q., & Shen, D. (2023). DoctorGLM: Fine-tuning your Chinese doctor is not a herculean task. 10.48550\/arXiv.2304.01097."},{"issue":"4","key":"10.1016\/j.ipm.2026.104784_bib0052","article-title":"RadBERT: Adapting transformer-based language models to radiology","volume":"4","author":"Yan","year":"2022","journal-title":"Radiology: Artificial Intelligence"},{"issue":"6","key":"10.1016\/j.ipm.2026.104784_bib0053","first-page":"2923","article-title":"Nested entity recognition approach in Chinese medical text","volume":"35","author":"Yan","year":"2024","journal-title":"Journal of Software"},{"issue":"10","key":"10.1016\/j.ipm.2026.104784_bib0054","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3689629","article-title":"Knowledge-injected prompt learning for Chinese biomedical entity normalization","volume":"23","author":"Yang","year":"2024","journal-title":"ACM Transactions on Asian and Low-Resource Language Information Processing"},{"key":"10.1016\/j.ipm.2026.104784_bib0055","series-title":"Proceedings of the 27th international conference on computational linguistics","first-page":"2159","article-title":"Distantly supervised NER with partial annotation learning and reinforcement learning","author":"Yang","year":"2018"},{"key":"10.1016\/j.ipm.2026.104784_bib0056","unstructured":"Yang, Z., Salakhutdinov, R., & Cohen, W. (2016). Multi-task cross-lingual sequence tagging from scratch. https:\/\/arxiv.org\/abs\/1603.06270v1."},{"key":"10.1016\/j.ipm.2026.104784_bib0057","doi-asserted-by":"crossref","DOI":"10.1016\/j.jbi.2024.104731","article-title":"Augmenting biomedical named entity recognition with general-domain resources","volume":"159","author":"Yin","year":"2024","journal-title":"Journal of Biomedical Informatics"},{"key":"10.1016\/j.ipm.2026.104784_bib0058","doi-asserted-by":"crossref","DOI":"10.1016\/j.jbi.2024.104731","article-title":"Augmenting biomedical named entity recognition with general-domain resources","volume":"159","author":"Yin","year":"2024","journal-title":"Journal of Biomedical Informatics"},{"key":"10.1016\/j.ipm.2026.104784_bib0059","unstructured":"Zeng, A., Liu, X., Du, Z., Wang, Z., Lai, H., Ding, M., Yang, Z., Xu, Y., Zheng, W., Xia, X., Tam, W. L., Ma, Z., Xue, Y., Zhai, J., Chen, W., Zhang, P., Dong, Y., & Tang, J. (2023). GLM-130B: An open bilingual pre-trained model. 10.48550\/arXiv.2210.02414."},{"issue":"8","key":"10.1016\/j.ipm.2026.104784_bib0060","first-page":"100","article-title":"Automatic recognition of chinese electronic medical record entities based on LLMs","volume":"9","author":"Zhang","year":"2025","journal-title":"Data Analysis and Knowledge Discovery"},{"issue":"1","key":"10.1016\/j.ipm.2026.104784_bib0061","first-page":"231","article-title":"Chinese medical named entity recognition based on prompt tuning and contrastive learning","volume":"62","author":"Zheng","year":"2025","journal-title":"Computer Engineering and Applications"},{"key":"10.1016\/j.ipm.2026.104784_bib0062","series-title":"Proceedings of the 40th annual meeting of the association for computational linguistics","first-page":"473","article-title":"Named entity recognition using an HMM-based chunk tagger","author":"Zhou","year":"2002"},{"key":"10.1016\/j.ipm.2026.104784_bib0063","unstructured":"Zhu, C., Cheng, Y., Gan, Z., Sun, S., Goldstein, T., & Liu, J. (2019). FreeLB: Enhanced adversarial training for natural language understanding. 10.48550\/arXiv.1909.11764."}],"container-title":["Information Processing & Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0306457326001755?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0306457326001755?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T14:38:04Z","timestamp":1783694284000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0306457326001755"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":63,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2026,11]]}},"alternative-id":["S0306457326001755"],"URL":"https:\/\/doi.org\/10.1016\/j.ipm.2026.104784","relation":{},"ISSN":["0306-4573"],"issn-type":[{"value":"0306-4573","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A hierarchical RL model for Chinese medical NER with radical semantics and dynamic decision","name":"articletitle","label":"Article Title"},{"value":"Information Processing & Management","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ipm.2026.104784","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"104784"}}