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Overcoming barriers to NLP for clinical text: the role of shared tasks and the need for additional creative solutions.克服临床文本自然语言处理的障碍：共享任务的作用及对其他创造性解决方案的需求。
J Am Med Inform Assoc. 2011 Sep-Oct;18(5):540-3. doi: 10.1136/amiajnl-2011-000465.
2
Natural language processing of symptoms documented in free-text narratives of electronic health records: a systematic review.电子健康记录中自由文本叙述的症状的自然语言处理：系统评价。
J Am Med Inform Assoc. 2019 Apr 1;26(4):364-379. doi: 10.1093/jamia/ocy173.
3
Designing an openEHR-Based Pipeline for Extracting and Standardizing Unstructured Clinical Data Using Natural Language Processing.设计一个基于 openEHR 的管道，使用自然语言处理提取和标准化非结构化临床数据。
Methods Inf Med. 2020 Dec;59(S 02):e64-e78. doi: 10.1055/s-0040-1716403. Epub 2020 Oct 14.
4
Extraction from Medical Records.从医疗记录中提取信息。
Stud Health Technol Inform. 2019;261:62-67.
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Combining text mining with clinical decision support in clinical practice: a scoping review.将文本挖掘与临床决策支持相结合在临床实践中的应用：范围综述。
J Am Med Inform Assoc. 2023 Feb 16;30(3):588-603. doi: 10.1093/jamia/ocac240.
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Development and evaluation of task-specific NLP framework in China.中国特定任务自然语言处理框架的开发与评估。
Stud Health Technol Inform. 2015;216:1031.
7
A systematic review of natural language processing and text mining of symptoms from electronic patient-authored text data.基于电子患者自报告文本数据的症状自然语言处理和文本挖掘的系统评价。
Int J Med Inform. 2019 May;125:37-46. doi: 10.1016/j.ijmedinf.2019.02.008. Epub 2019 Feb 20.
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Inventory of tools for Dutch clinical language processing.荷兰临床语言处理工具清单。
Stud Health Technol Inform. 2012;180:245-9.
9
Longitudinal analysis of pain in patients with metastatic prostate cancer using natural language processing of medical record text.利用医疗记录文本的自然语言处理技术对转移性前列腺癌患者的疼痛进行纵向分析。
J Am Med Inform Assoc. 2013 Sep-Oct;20(5):898-905. doi: 10.1136/amiajnl-2012-001076. Epub 2012 Nov 9.
10
Scaling-up NLP Pipelines to Process Large Corpora of Clinical Notes.扩大自然语言处理管道以处理大量临床记录语料库。
Methods Inf Med. 2015;54(6):548-52. doi: 10.3414/ME14-02-0018. Epub 2015 Nov 4.
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Enhancing the Utility of Health Related Quality of Life (HRQoL) Assessment Tools in Abdominal Wall Hernia (AWH) Surgery Through Artificial Intelligence (AI): A Framework Proposal.通过人工智能（AI）提高腹壁疝（AWH）手术中健康相关生活质量（HRQoL）评估工具的效用：一项框架提案。
J Abdom Wall Surg. 2025 Aug 13;4:14952. doi: 10.3389/jaws.2025.14952. eCollection 2025.
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Large language models for clinical decision support in gastroenterology and hepatology.用于胃肠病学和肝病学临床决策支持的大语言模型
Nat Rev Gastroenterol Hepatol. 2025 Aug 22. doi: 10.1038/s41575-025-01108-1.
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Synthetic data distillation enables the extraction of clinical information at scale.合成数据提炼能够大规模提取临床信息。
NPJ Digit Med. 2025 May 10;8(1):267. doi: 10.1038/s41746-025-01681-4.
4
Assessing Total Hip Arthroplasty Outcomes and Generating an Orthopedic Research Outcome Database via a Natural Language Processing Pipeline: Development and Validation Study.通过自然语言处理管道评估全髋关节置换术结果并生成骨科研究结果数据库：开发与验证研究
JMIR Med Inform. 2025 Mar 12;13:e64705. doi: 10.2196/64705.
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Considerations and Challenges When Using Clinical and Vital Record Review for Suicide Research.使用临床和生命记录回顾进行自杀研究时的注意事项与挑战。
J Patient Saf. 2025 Apr 1;21(3):e8-e17. doi: 10.1097/PTS.0000000000001325. Epub 2025 Feb 11.
6
Privacy-preserving large language models for structured medical information retrieval.用于结构化医学信息检索的隐私保护大语言模型
NPJ Digit Med. 2024 Sep 20;7(1):257. doi: 10.1038/s41746-024-01233-2.
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Near Real-Time Syndromic Surveillance of Emergency Department Triage Texts Using Natural Language Processing: Case Study in Febrile Convulsion Detection.使用自然语言处理技术对急诊科分诊文本进行近实时症状监测：热性惊厥检测案例研究
JMIR AI. 2024 Aug 30;3:e54449. doi: 10.2196/54449.
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Is Boundary Annotation Necessary? Evaluating Boundary-Free Approaches to Improve Clinical Named Entity Annotation Efficiency: Case Study.边界标注是否必要？评估无边界方法以提高临床命名实体标注效率：案例研究
JMIR Med Inform. 2024 Jul 2;12:e59680. doi: 10.2196/59680.
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Exploring the Latest Highlights in Medical Natural Language Processing across Multiple Languages: A Survey.探索多语言医学自然语言处理的最新亮点：综述。
Yearb Med Inform. 2023 Aug;32(1):230-243. doi: 10.1055/s-0043-1768726. Epub 2023 Dec 26.
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Rehabilitation Treatment Specification System for Voice Therapy: Application to Everyday Clinical Care.嗓音治疗康复治疗规范系统：在日常临床护理中的应用。
Am J Speech Lang Pathol. 2024 Mar 7;33(2):814-830. doi: 10.1044/2023_AJSLP-23-00283. Epub 2023 Dec 19.
本文引用的文献
1
Natural language processing: an introduction.自然语言处理：入门。
J Am Med Inform Assoc. 2011 Sep-Oct;18(5):544-51. doi: 10.1136/amiajnl-2011-000464.
2
2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text.2010 i2b2/VA 挑战赛：临床文本中的概念、断言和关系
J Am Med Inform Assoc. 2011 Sep-Oct;18(5):552-6. doi: 10.1136/amiajnl-2011-000203. Epub 2011 Jun 16.
3
Extracting medication information from clinical text.从临床文本中提取药物信息。
J Am Med Inform Assoc. 2010 Sep-Oct;17(5):514-8. doi: 10.1136/jamia.2010.003947.
4
Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications.梅奥临床文本分析和知识提取系统（cTAKES）：架构、组件评估和应用。
J Am Med Inform Assoc. 2010 Sep-Oct;17(5):507-13. doi: 10.1136/jamia.2009.001560.
5
Closing the gap between NLP research and clinical practice.缩小自然语言处理研究与临床实践之间的差距。
Methods Inf Med. 2010;49(4):317-9.
6
Evaluation of a generalizable approach to clinical information retrieval using the automated retrieval console (ARC).使用自动化检索控制台 (ARC) 评估一种通用的临床信息检索方法。
J Am Med Inform Assoc. 2010 Jul-Aug;17(4):375-82. doi: 10.1136/jamia.2009.001412.
7
Recognizing obesity and comorbidities in sparse data.在稀疏数据中识别肥胖及合并症。
J Am Med Inform Assoc. 2009 Jul-Aug;16(4):561-70. doi: 10.1197/jamia.M3115. Epub 2009 Apr 23.
8
Introducing meta-services for biomedical information extraction.介绍用于生物医学信息提取的元服务。
Genome Biol. 2008;9 Suppl 2(Suppl 2):S6. doi: 10.1186/gb-2008-9-s2-s6. Epub 2008 Sep 1.
9
Identifying patient smoking status from medical discharge records.从医疗出院记录中识别患者的吸烟状况。
J Am Med Inform Assoc. 2008 Jan-Feb;15(1):14-24. doi: 10.1197/jamia.M2408. Epub 2007 Oct 18.
10
Evaluating the state-of-the-art in automatic de-identification.评估自动去识别技术的最新进展。
J Am Med Inform Assoc. 2007 Sep-Oct;14(5):550-63. doi: 10.1197/jamia.M2444. Epub 2007 Jun 28.
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