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Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program
1National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. alan@nlm.nih.gov
Proceedings. AMIA Symposium
|February 5, 2002
Summary
MetaMap effectively maps biomedical text to the Unified Medical Language System (UMLS) Metathesaurus. This program enhances information retrieval and data mining by leveraging natural language processing for biomedical concept discovery.
Area of Science:
- Biomedical Informatics
- Natural Language Processing
Background:
- The Unified Medical Language System (UMLS) Metathesaurus is a crucial resource for biomedical knowledge representation.
- Effective access to this knowledge is vital for applications like decision support, record management, information retrieval (IR), and data mining.
Purpose of the Study:
- To describe MetaMap, a program developed by the National Library of Medicine (NLM).
- To explain MetaMap's function in mapping biomedical text to the UMLS Metathesaurus and discovering Metathesaurus concepts within text.
Main Methods:
- Utilizes a knowledge-intensive approach.
- Employs symbolic, natural language processing (NLP), and computational linguistic techniques.
Main Results:
- MetaMap successfully maps biomedical text to the UMLS Metathesaurus.
- Enables the discovery of Metathesaurus concepts referenced in text.
Conclusions:
- MetaMap is a foundational tool for NLM's Indexing Initiative System.
- Supports both semi-automatic and fully automatic indexing of biomedical literature.