The DOI matches its Crossref record; 17 of the 18 references it cites were found in a registry or an index.
MedScan, a natural language processing engine for MEDLINE abstracts
Open accessAbstract
MOTIVATION: The importance of extracting biomedical information from scientific publications is well recognized. A number of information extraction systems for the biomedical domain have been reported, but none of them have become widely used in practical applications. Most proposals to date make rather simplistic assumptions about the syntactic aspect of natural language. There is an urgent need for a system that has broad coverage and performs well in real-text applications. RESULTS: We present a general biomedical domain-oriented NLP engine called MedScan that efficiently processes sentences from MEDLINE abstracts and produces a set of regularized logical structures representing the meaning of each sentence. The engine utilizes a specially developed context-free grammar and lexicon. Preliminary evaluation of the system's performance, accuracy, and coverage exhibited encouraging results. Further approaches for increasing the coverage and reducing parsing ambiguity of the engine, as well as its application for information extraction are discussed.
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1 of the 18 references couldn’t be matched to a known paper.
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Metadata
- Authors
- Novichkova, S., Egorov, S., & Daraselia, N.
- Affiliations
- Ariadne Diagnostics (United States) (US)
- Corresponding author
- Novichkova, Svetlana
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2003-09-01
- Volume
- 19
- Issue
- 13
- Pages
- 1699-1706
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2140601463
- Cited by
- 236
- References
- 18
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 5 · 2023: 4 · 2022: 13 · 2021: 6 · 2020: 7 · 2019: 10 · 2018: 6 · 2017: 5 · 2016: 11 · 2015: 7 · 2014: 14 · 2013: 12 · 2012: 12
- FWCI
- 5.30
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Bioinformatics (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Biomedical Text Mining and Ontologies
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Advanced Text Analysis Techniques
- Keywords
- MEDLINE abstracts, biomedical information extraction, natural language processing, context-free grammars, vocabulary, logical structure
- MeSH terms
- Abstracting and Indexing, Artificial Intelligence, Database Management Systems, Natural Language Processing, Pattern Recognition, Automated, Periodicals as Topic, Subject Headings, MEDLINE, Information Storage and Retrieval, Vocabulary, Controlled
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