MetaMap精简版：对MetaMap新Java实现的评估
MetaMap Lite: an evaluation of a new Java implementation of MetaMap.
作者信息
Demner-Fushman Dina, Rogers Willie J, Aronson Alan R
机构信息
Lister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA.
出版信息
J Am Med Inform Assoc. 2017 Jul 1;24(4):841-844. doi: 10.1093/jamia/ocw177.
Abstract
MetaMap is a widely used named entity recognition tool that identifies concepts from the Unified Medical Language System Metathesaurus in text. This study presents MetaMap Lite, an implementation of some of the basic MetaMap functions in Java. On several collections of biomedical literature and clinical text, MetaMap Lite demonstrated real-time speed and precision, recall, and F1 scores comparable to or exceeding those of MetaMap and other popular biomedical text processing tools, clinical Text Analysis and Knowledge Extraction System (cTAKES) and DNorm.
摘要
MetaMap是一种广泛使用的命名实体识别工具，可从文本中的统一医学语言系统叙词表中识别概念。本研究展示了MetaMap Lite，它是MetaMap一些基本功能的Java实现。在几个生物医学文献和临床文本集合上，MetaMap Lite展示了实时速度以及与MetaMap和其他流行的生物医学文本处理工具（临床文本分析与知识提取系统（cTAKES）和DNorm）相当或更高的精确率、召回率和F1分数。
相似文献
1
MetaMap Lite: an evaluation of a new Java implementation of MetaMap.MetaMap精简版：对MetaMap新Java实现的评估
J Am Med Inform Assoc. 2017 Jul 1;24(4):841-844. doi: 10.1093/jamia/ocw177.
2
Use of "off-the-shelf" information extraction algorithms in clinical informatics: A feasibility study of MetaMap annotation of Italian medical notes.临床信息学中“现成可用”信息提取算法的应用：意大利医学记录的MetaMap注释可行性研究。
J Biomed Inform. 2016 Oct;63:22-32. doi: 10.1016/j.jbi.2016.07.017. Epub 2016 Jul 18.
3
4
Sophia: A Expedient UMLS Concept Extraction Annotator.索菲亚：一种便捷的统一医学语言系统概念提取注释器。
AMIA Annu Symp Proc. 2014 Nov 14;2014:467-76. eCollection 2014.
5
Mining biomedical data using MetaMap Transfer (MMtx) and the Unified Medical Language System (UMLS).使用MetaMap Transfer（MMtx）和统一医学语言系统（UMLS）挖掘生物医学数据。
Methods Mol Biol. 2007;408:153-69. doi: 10.1007/978-1-59745-547-3_9.
6
Comparison of MetaMap and cTAKES for entity extraction in clinical notes.比较 MetaMap 和 cTAKES 在临床记录中的实体提取。
BMC Med Inform Decis Mak. 2018 Sep 14;18(Suppl 3):74. doi: 10.1186/s12911-018-0654-2.
7
A normalized lexical lookup approach to identifying UMLS concepts in free text.一种用于在自由文本中识别统一医学语言系统（UMLS）概念的规范化词汇查找方法。
Stud Health Technol Inform. 2007;129(Pt 1):545-9.
8
Natural language processing (NLP) tools in extracting biomedical concepts from research articles: a case study on autism spectrum disorder.自然语言处理（NLP）工具在从研究文章中提取生物医学概念中的应用：以自闭症谱系障碍为例。
BMC Med Inform Decis Mak. 2020 Dec 30;20(Suppl 11):322. doi: 10.1186/s12911-020-01352-2.
9
Assessment of disease named entity recognition on a corpus of annotated sentences.基于带注释句子语料库的疾病命名实体识别评估。
BMC Bioinformatics. 2008 Apr 11;9 Suppl 3(Suppl 3):S3. doi: 10.1186/1471-2105-9-S3-S3.
10
MetaMap Lite in Excel: Biomedical Named-Entity Recognition for Non-Technical Users.Excel 中的 MetaMap Lite：面向非技术用户的生物医学命名实体识别
Stud Health Technol Inform. 2017;245:1252.
引用本文的文献
1
MPSE identifies newborns for whole genome sequencing within 48 h of NICU admission.MPSE在新生儿重症监护病房（NICU）入院48小时内识别出进行全基因组测序的新生儿。
NPJ Genom Med. 2025 Jun 12;10(1):47. doi: 10.1038/s41525-025-00506-3.
2
Hybrid natural language processing tool for semantic annotation of medical texts in Spanish.用于西班牙语医学文本语义标注的混合自然语言处理工具。
BMC Bioinformatics. 2025 Jan 8;26(1):7. doi: 10.1186/s12859-024-05949-6.
3
Protocol for Designing a Model to Predict the Likelihood of Psychosis From Electronic Health Records Using Natural Language Processing and Machine Learning.使用自然语言处理和机器学习从电子健康记录中设计预测精神病可能性模型的方案
Perm J. 2024 Sep 16;28(3):23-36. doi: 10.7812/TPP/23.139. Epub 2024 Sep 2.
4
On the role of the UMLS in supporting diagnosis generation proposed by Large Language Models.在支持大型语言模型提出的诊断生成中 UMLS 的作用。
J Biomed Inform. 2024 Sep;157:104707. doi: 10.1016/j.jbi.2024.104707. Epub 2024 Aug 13.
5
A Comprehensive Evaluation of Biomedical Entity Linking Models.生物医学实体链接模型的综合评估
Proc Conf Empir Methods Nat Lang Process. 2023 Dec;2023:14462-14478. doi: 10.18653/v1/2023.emnlp-main.893.
6
MetaTron: advancing biomedical annotation empowering relation annotation and collaboration.MetaTron：推进生物医学标注，赋能关系标注与协作。
BMC Bioinformatics. 2024 Mar 14;25(1):112. doi: 10.1186/s12859-024-05730-9.
7
Natural language processing of clinical notes enables early inborn error of immunity risk ascertainment.临床记录的自然语言处理能够实现先天性免疫缺陷风险的早期判定。
J Allergy Clin Immunol Glob. 2024 Feb 2;3(2):100224. doi: 10.1016/j.jacig.2024.100224. eCollection 2024 May.
8
The SMART Text2FHIR Pipeline.SMART 文本到 FHIR 管道。
AMIA Annu Symp Proc. 2024 Jan 11;2023:514-520. eCollection 2023.
9
Primary care detection of cognitive impairment leveraging health and consumer technologies in underserved US communities: protocol for a pragmatic randomised controlled trial of the MyCog paradigm.利用健康和消费者技术在服务不足的美国社区进行初级保健认知障碍检测：MyCog 范式的实用随机对照试验方案。
BMJ Open. 2023 Oct 18;13(10):e080101. doi: 10.1136/bmjopen-2023-080101.
10
Extracting Complementary and Integrative Health Approaches in Electronic Health Records.从电子健康记录中提取补充和综合健康方法。
J Healthc Inform Res. 2023 Aug 17;7(3):277-290. doi: 10.1007/s41666-023-00137-2. eCollection 2023 Sep.
本文引用的文献
1
CD-REST: a system for extracting chemical-induced disease relation in literature.CD-REST：一种用于从文献中提取化学物质诱发疾病关系的系统。
Database (Oxford). 2016 Mar 25;2016. doi: 10.1093/database/baw036. Print 2016.
2
Towards a Generalizable Time Expression Model for Temporal Reasoning in Clinical Notes.迈向临床笔记中时间推理的通用时间表达模型。
AMIA Annu Symp Proc. 2015 Nov 5;2015:1252-9. eCollection 2015.
3
NOBLE - Flexible concept recognition for large-scale biomedical natural language processing.NOBLE——用于大规模生物医学自然语言处理的灵活概念识别
BMC Bioinformatics. 2016 Jan 14;17:32. doi: 10.1186/s12859-015-0871-y.
4
Challenges in clinical natural language processing for automated disorder normalization.临床自然语言处理中自动疾病标准化的挑战。
J Biomed Inform. 2015 Oct;57:28-37. doi: 10.1016/j.jbi.2015.07.010. Epub 2015 Jul 14.
5
NCBI disease corpus: a resource for disease name recognition and concept normalization.NCBI疾病语料库：一种用于疾病名称识别和概念规范化的资源。
J Biomed Inform. 2014 Feb;47:1-10. doi: 10.1016/j.jbi.2013.12.006. Epub 2014 Jan 3.
6
DNorm: disease name normalization with pairwise learning to rank.DNorm：基于对分学习排序的疾病名称标准化。
Bioinformatics. 2013 Nov 15;29(22):2909-17. doi: 10.1093/bioinformatics/btt474. Epub 2013 Aug 21.
7
MEDIC: a practical disease vocabulary used at the Comparative Toxicogenomics Database.医学：比较毒理学基因组学数据库中使用的实用疾病词汇。
Database (Oxford). 2012 Mar 20;2012:bar065. doi: 10.1093/database/bar065. Print 2012.
8
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.
9
The Yale cTAKES extensions for document classification: architecture and application.耶鲁 CTakes 扩展用于文档分类：架构与应用。
J Am Med Inform Assoc. 2011 Sep-Oct;18(5):614-20. doi: 10.1136/amiajnl-2011-000093. Epub 2011 May 27.
10
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.
Zotero 插件