[1] 施榕, 郭爱民.全科医生科研方法[M].北京: 人民卫生出版社, 2017: 211-219.(SHI R, GUO A M.Research methods of general practitioners[M].Beijing: People’s Medical Publishing House, 2017: 211-219.)
[2] ZHU M, HONG R H, YANG T, et al.The efficacy of measurement based care for depressive disorders: Systematic review and meta-analysis of randomized controlled trials[J].The journal of clinical psychiatry, 2021, 82(5): 21r14034.
[3] U.S.Food and Drug Administration.Patient-reported outcome measures: use in medical product development to support labeling claims[EB/OL].[2024-07-28].https: //www.fda.gov/regulatory-information/search-fda-guidance-documents
[4] DEVELLIS R F.Scale development: Theory and applications[M].4th ed.Los Angeles: SAGE, 2017.
[5] CELLA D, YOUNT S, ROTHROCK N, et al.The patient-reported outcomes measurement information system (PROMIS): progress of an NIH roadmap cooperative group during its first two years[J].Medical care, 2007, 45(5 Suppl 1): S3-S11.
[6] NLM.NIH CDE repository[EB/OL].[2024-08-02].https: //cde.nlm.nih.gov/form/search.
[7] ZHAO W X, ZHOU K, LI J Y, et al.A survey of large language models[J].arXiv preprint arXiv: 2303.18223, 2023.
[8] GOEL A, GUETA A, GILON O, et al.LLMs accelerate annotation for medical information extraction[C]//Machine learning for health (ML4H).New York: PMLR, 2023: 82-100.
[9] WAN Z, CHENG F, MAO Z, et al.GPT-RE: In-context learning for relation extraction using large language models[J].arXiv preprint arXiv: 2305.02105, 2023.
[10] 杨冬菊, 黄俊涛.基于大语言模型的中文科技文献标注方法[J/OL].计算机工程: 1-7[2024-03-30].https: //doi.org/10.19678/j.issn.1000-3428.0068400.(YANG D G, HUANG J T.Workshop on enterprise knowledge graphs using large language models[J/OL].Computer engineering, 1-7[2024-03-30].https: //doi.org/10.19678/j.issn.1000-3428.0068400.)
[11] KARAN S, TAO T, JURAJ G, et al.Towards expert-level medical question answering with large language models[J].arXiv preprint arXiv: 2305.09617, 2023.
[12] FREY J, MEYER L P, ARNDT N, et al.Benchmarking the abilities of large language models for RDF knowledge graph creation and comprehension: how well do LLMs speak turtle?[J].arXiv preprint arXiv: 2309.17122, 2023.
[13] KUMAR A H S.Analysis of ChatGPT tool to assess the potential of its utility for academic writing in biomedical domain[J].Biology, engineering, medicine and science reports, 2023, 9(1): 24-30.
[14] MANNING C D.Human language understanding & reasoning [J].Daedalus, 2022, 151(2): 127-138.
[15] TOUVRON H, LAVRIL T, IZACARD G, et al.LLaMA: open and efficient foundation language models[J].arXiv preprint arXiv: 2302.13971, 2023.
[16] LIU P, YUAN W, FU J, et al.Pre-train, prompt, and predict: a systematic survey of prompting methods in natural language processing[J].ACM computing surveys, 2023, 55(9): 1-35.
[17] HAN X, ZHANG Z, DING N, et al.Pre-trained models: past, present and future[J].arXiv preprint arXiv: 2106.07139, 2021.
[18] CHENG P, Xi Y, AOKUN C, et al.A study of generative large language model for medical research and healthcare[J].arXiv preprint arXiv: 2305.13523, 2023.
[19] 马武仁, 弓孟春, 戴辉, 等.以ChatGPT为代表的大语言模型在临床医学中的应用综述[J].医学信息学杂志, 2023, 44(7): 9-17.(MA W R, GONG M C, DAI H, et al.A comprehensive review of the applications of large language models in clinical medicine with ChatGPT as a representative[J].Journal of medical informatics, 2023, 44(7): 9-17.)
[20] MONICA A, STEFAN H, HUNTER L, et al.Large language models are few-shot clinical information extractors[C]//Proceedings of the 2022 conference on empirical methods in natural language processing.Abu Dhabi: ACL, 2022: 1998-2022.
[21] PENG C, YANG X, CHEN A, et al.A study of generative large language model for medical research and healthcare[J].NPJ digital medicine, 2023, 6(1): 210.
[22] AGRAWAL M, HEGSELMANN S, LANG H, et al.Large language models are few-shot clinical information extractors[J].arXiv preprint arXiv: 2205.12689, 2022.
[23] MIWA M, BANSAL M.End-to-end relation extraction using LSTMs on sequences and tree structures[J].arXiv preprint arXiv: 1601.00770, 2016.
[24] BEKOULIS G, DELEU J, DEMEESTER T, et al.Joint entity recognition and relation extraction as a multi-head selection problem[J].Expert systems with applications, 2018, 114: 34-45.
[25] LUAN Y, HE L, OSTENDORF M, et al.Multi-task identification of entities, relations, and coreference for scientific knowledge graph construction[J].arXiv preprint arXiv: 1808.09602, 2018.
[26] 杨波, 孙晓虎, 党佳怡, 等.面向医疗问答系统的大语言模型命名实体识别方法[J].计算机科学与探索, 2023, 17(10): 2389.(YANG B, SUN X H, DANG J Y, et al.Named entity recognition method of large language model for medical question answering system[J].Journal of frontiers of computer science and technology, 2023, 17(10): 2389.)
[27] SUN X, LI X, LI J, ET A L.Text classification via large language models[J].arXiv preprint arXiv: 2305.08377, 2023.
[28] ONG J, KEDIA N, HARIHAR S, et al.Applying large language model artificial intelligence for retina international classification of diseases (ICD) coding[J].Journal of medical artificial intelligence, 2023, 6: 21.
[29] WU L I, LI G.Zero-shot construction of Chinese medical knowledge graph with ChatGPT[C]//2023 IEEE international conference on medical artificial intelligence (MedAI).Beijing: IEEE, 2023: 278-283.
[30] ZHU Y, WANG X, CHEN J, et al.LLMs for knowledge graph construction and reasoning: Recent capabilities and future opportunities[J].arXiv preprint arXiv: 2305.13168, 2023.
[31] ZHU W, WANG X, CHEN M, et al.Overview of the PromptCBLUE shared tTask in CHIP2023[J].arXiv preprint arXiv: 2312.17522, 2023.
[32] LI B, FANG G, YANG Y, et al.Evaluating ChatGPT’s information extraction capabilities: an assessment of performance, explainability, calibration, and faithfulness[J].arXiv preprint arXiv: 2304.11633, 2023.
[33] WEI X, CUI X, CHENG N, et al.Zero-shot information extraction via chatting with ChatGPT[J].arXiv preprint arXiv: 2302.10205, 2023.
[34] MIALON, G.DESSÌ R, LOMELI M, et al.Augmented language models: A survey[J].arXiv preprint arXiv: 2302.07842, 2023.
[35] DUNN A, DAGDELEN J, WALKER N, et al.Structured information extraction from complex scientific text with fine-tuned large language models[J].arXiv preprint arXiv: 2212.05238, 2022.
[36] ZHENG C, GUO C Y.A pattern-first pipeline approach for entity and relation extraction[J].Neurocomputing, 2022(494): 182-191.
[37] XUE L L, ZHANG D, DONG Y X, et al.AutoRE: Document-level relation extraction with large language models[J].arXiv preprint arXiv: 2403.14888, 2024.
[38] 孙海霞, 郝洁, 郭臻, 等.基于知识元的细粒度医学量表文档知识表示框架构建[J].数字图书馆论坛, 2023, 19(12): 86-98.(SUN H X, HAO J, GUO Z, et al.Construction of a fine-grained knowledge element-based framework for knowledge representation in medical scale documents[J].Digital library forum, 2023, 19(12): 86-98.)
[39] 戴晓阳.常用心理评估量表手册[M].修订版.北京: 人民军医出版社, 2015: 150-154.(DAI X Y.Handbook of commonly used psychological assessment scales[M].Revised ed.Beijing: People’s Military Medical Publishing House, 2015: 150-154.)
[40] HUANG J W, YANG D H M, RONG R C, et al.A critical assessment of using ChatGPT for extracting structured data from clinical notes[J].NPJ digital medicine, 2024(7): 106.
[41] LANDIS J R, KOCH G G.The measurement of observer agreement for categorical data[J].Biometrics, 33(1): 159-174.
[42] NG A, FULFORD L.ChatGPT prompt engineering for developers[EB/OL].[2024-08-03].https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/.
[43] YUAN W, NEUBIG G, LIU P.Bartscore: Evaluating generated text as text generation[C]//Proceedings of the 34th international conference on neural information processing systems.New York: Curran Associates, 2021.
[44] CHEN J, LIU L, RUAN S, et al.Are different versions of ChatGPT’s ability comparable to the clinical diagnosis presented in case reports? a descriptive study[J].Journal of multidisciplinary healthcare, 2023, 16: 3825-3831.