{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T11:29:54Z","timestamp":1771500594253,"version":"3.50.1"},"reference-count":74,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Yunling Scholar Talent Program of Yunnan Province","award":["K264202230207"],"award-info":[{"award-number":["K264202230207"]}]},{"name":"Deng Cheng Expert Workstation of Yunnan Province","award":["202305AF150202"],"award-info":[{"award-number":["202305AF150202"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Emerg. Top. Comput. Intell."],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1109\/tetci.2025.3567602","type":"journal-article","created":{"date-parts":[[2025,6,2]],"date-time":"2025-06-02T14:03:52Z","timestamp":1748873032000},"page":"4051-4065","source":"Crossref","is-referenced-by-count":1,"title":["Fine-Tuning LLMs for Anesthesiology via Compositional Data Generation"],"prefix":"10.1109","volume":"9","author":[{"given":"Yanhong","family":"Li","sequence":"first","affiliation":[{"name":"School of Information Science and Engineering, Yunnan University, Kunming, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3180-0484","authenticated-orcid":false,"given":"Yibing","family":"Zhan","sequence":"additional","affiliation":[{"name":"Yunnan United Vision Technology Company Ltd., Kunming, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0761-7893","authenticated-orcid":false,"given":"Baosheng","family":"Yu","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore"}]},{"given":"Zhonghai","family":"Wang","sequence":"additional","affiliation":[{"name":"China University of Petroleum (East China), Qingdao, China"}]},{"given":"Chong","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Yunnan University, Kunming, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-5805-2757","authenticated-orcid":false,"given":"Da","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Yunnan University, Kunming, China"}]},{"given":"Chengli","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Yunnan University, Kunming, China"}]},{"given":"Bohao","family":"Zhou","sequence":"additional","affiliation":[{"name":"China University of Petroleum (East China), Qingdao, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8976-2084","authenticated-orcid":false,"given":"Liang","family":"Ding","sequence":"additional","affiliation":[{"name":"Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5388-9080","authenticated-orcid":false,"given":"Weifeng","family":"Liu","sequence":"additional","affiliation":[{"name":"China University of Petroleum (East China), Qingdao, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-0045-8724","authenticated-orcid":false,"given":"Xiongbing","family":"Wang","sequence":"additional","affiliation":[{"name":"The Second Affiliated Hospital of Kunming Medical University, Kunming, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0783-5273","authenticated-orcid":false,"given":"Dapeng","family":"Tao","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Yunnan University, Kunming, China"}]}],"member":"263","reference":[{"key":"ref1","article-title":"A survey of large language models","author":"Zhao","year":"2023"},{"key":"ref2","article-title":"BianQue: Balancing the questioning and suggestion ability of health LLMs with multi-turn health conversations polished by ChatGPT","author":"Chen","year":"2023"},{"key":"ref3","article-title":"DISC-MedLLM: Bridging general large language models and real-world medical consultation","author":"Bao","year":"2023","journal-title":"CoRR"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.findings-emnlp.725"},{"key":"ref5","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2025.102963","article-title":"A survey of large language models for healthcare: From data, technology, and applications to accountability and ethics","volume":"118","author":"He","year":"2025","journal-title":"Inf. Fusion"},{"key":"ref6","article-title":"A survey of large language models in medicine: Progress, application, and challenge","author":"Zhou","year":"2023"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-long.754"},{"key":"ref8","article-title":"HuatuoGPT-II, one-stage training for medical adaption of LLMs","author":"Chen","year":"2023"},{"key":"ref9","article-title":"HuaTuo: Tuning llama model with Chinese medical knowledge","author":"Wang","year":"2023"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.7759\/cureus.40895"},{"key":"ref11","article-title":"DoctorGLM: Fine-tuning your Chinese doctor is not a herculean task","author":"Xiong","year":"2023"},{"key":"ref12","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2024.108290","article-title":"Medchatzh: A tuning LLM for traditional chinese medicine consultations","volume":"172","author":"Tan","year":"2024","journal-title":"Comput. Biol. Med."},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i17.29907"},{"key":"ref14","first-page":"27730","article-title":"Training language models to follow instructions with human feedback","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"35","author":"Ouyang","year":"2022"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.emnlp-main.385"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-019-3119-4"},{"key":"ref17","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.129389","article-title":"Hypnos: A domain-specific large language model for anesthesiology","volume":"624","author":"Wang","year":"2025","journal-title":"Neurocomputing"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1810.04805"},{"key":"ref19","article-title":"RoBERTa: A robustly optimized BERT pretraining approach","author":"Liu","year":"2019"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s13042-024-02443-6"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2024.3372442"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2020.3040444"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2024.3369478"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2023.3301774"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1525\/9780520940420-020"},{"key":"ref26","article-title":"DeBERTa: Decoding-enhanced BERT with disentangled attention","author":"He","year":"2020"},{"key":"ref27","article-title":"ELECTRA: Pre-training text encoders as discriminators rather than generators","author":"Clark","year":"2020"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.aiopen.2021.07.001"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.aiopen.2021.12.003"},{"key":"ref30","article-title":"ERNIE: Enhanced representation through knowledge integration","author":"Sun","year":"2019"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i05.6428"},{"key":"ref32","article-title":"ERNIE 3.0: Large-scale knowledge enhanced pre-training for language understanding and generation","author":"Sun","year":"2021"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-long.26"},{"key":"ref34","article-title":"GLM-130B: An open bilingual pre-trained model","author":"Zeng","year":"2022"},{"issue":"140","key":"ref35","first-page":"1","article-title":"Exploring the limits of transfer learning with a unified text-to-text transformer","volume":"21","author":"Raffel","year":"2020","journal-title":"J. Mach. Learn. Res."},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-024-02199-0"},{"key":"ref37","article-title":"GPT-4 technical report","author":"Achiam","year":"2023"},{"issue":"240","key":"ref38","first-page":"1","article-title":"PaLM: Scaling language modeling with pathways","volume":"24","author":"Chowdhery","year":"2023","journal-title":"J. Mach. Learn. Res."},{"key":"ref39","article-title":"PaLM 2 technical report","author":"Anil","year":"2023"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.bigscience-1.9"},{"key":"ref41","article-title":"LLaMA: Open and efficient foundation language models","author":"Touvron","year":"2023"},{"key":"ref42","article-title":"LLaMA 2: Open foundation and fine-tuned chat models","author":"Touvron","year":"2023"},{"key":"ref43","article-title":"Baichuan 2: Open large-scale language models","author":"Yang","year":"2023"},{"key":"ref44","article-title":"Qwen technical report","author":"Bai","year":"2023"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2023.3311333"},{"issue":"PMLR","key":"ref46","first-page":"239","article-title":"CEHR-BERT: Incorporating temporal information from structured EHR data to improve prediction tasks","volume-title":"Proc. Mach. Learn. Health","author":"Pang","year":"2021"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-021-00455-y"},{"key":"ref48","article-title":"ClinicalBERT: Modeling clinical notes and predicting hospital readmission","author":"Huang","year":"2019"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-023-06291-2"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-024-03423-7"},{"key":"ref51","article-title":"MedAlpacaan open-source collection of medical conversational AI models and training data","author":"Han","year":"2023"},{"key":"ref52","article-title":"Clinical camel: An open-source expert-level medical language model with dialogue-based knowledge encoding","author":"Toma","year":"2023"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.findings-emnlp.83"},{"key":"ref54","article-title":"Radiology-LLaMA2: Best-in-class large language model for radiology","author":"Liu","year":"2023"},{"key":"ref55","article-title":"A survey of hallucination in large foundation models","author":"Rawte","year":"2023"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01070"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/tmm.2025.3535292"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-025-02348-z"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-020-01412-0"},{"key":"ref60","first-page":"55734","article-title":"Large language model as attributed training data generator: A tale of diversity and bias","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"36","author":"Yu","year":"2024"},{"key":"ref61","first-page":"14179","article-title":"Seen to unseen: Exploring compositional generalization of multi-attribute controllable dialogue generation","author":"Zeng","year":"2023"},{"key":"ref62","first-page":"2511","article-title":"Principle-driven self-alignment of language models from scratch with minimal human supervision","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"36","author":"Sun","year":"2024"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1186\/s12911-019-0761-8"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2883637"},{"key":"ref65","article-title":"ChatMed: A Chinese medical large language model","author":"Zhu","year":"2023"},{"key":"ref66","volume-title":"Yao & Artusio\u2019s Anesthesiology: Problem-Oriented Patient Management","author":"Fun-Sun","year":"2011"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.3115\/1073083.1073135"},{"key":"ref68","first-page":"74","article-title":"ROUGE: A package for automatic evaluation of summaries","volume-title":"Text Summarization Branches Out","author":"Lin","year":"2004"},{"key":"ref69","first-page":"110","article-title":"A diversity promoting objectiv function for neural conversation models","volume-title":"Proc. Conf. North Amer. Chapter Assoc. Comput. Linguistics: Human Lang. Technol.","author":"Li","year":"2016"},{"key":"ref70","first-page":"344","article-title":"GLEU: Automatic evaluation of sentence-level fluency","volume-title":"Proc. 45th Annu. Meeting Assoc. Comput. Linguistics","author":"Mutton","year":"2007"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.emnlp-main.153"},{"key":"ref72","article-title":"BooookScore: A systematic exploration of book-length summarization in the era of LLMs","author":"Chang","year":"2023"},{"key":"ref73","article-title":"A survey on retrieval-augmented text generation","author":"Li","year":"2022"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1145\/3664647.3681584"}],"container-title":["IEEE Transactions on Emerging Topics in Computational Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/7433297\/11267152\/11018356.pdf?arnumber=11018356","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T19:06:06Z","timestamp":1764183966000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11018356\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12]]},"references-count":74,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tetci.2025.3567602","relation":{},"ISSN":["2471-285X"],"issn-type":[{"value":"2471-285X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12]]}}}