MedScan, a natural language processing engine for MEDLINE abstracts

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 ra...

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Vydané v:Bioinformatics Ročník 19; číslo 13; s. 1699 - 1706
Hlavní autori: Novichkova, Svetlana, Egorov, Sergei, Daraselia, Nikolai
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Oxford Oxford University Press 01.09.2003
Oxford Publishing Limited (England)
Predmet:
Abstracting and Indexing as Topic - methods
Artificial Intelligence
Biological and medical sciences
Database Management Systems
Fundamental and applied biological sciences. Psychology
General aspects
Information Storage and Retrieval - methods
Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)
MEDLINE
Natural Language Processing
Pattern Recognition, Automated
Periodicals as Topic
Subject Headings
Vocabulary, Controlled
Performance evaluation
Language processing
Computer program
Abstract
Extraction
Data mining
Bioinformatics
ISSN:1367-4803, 1460-2059, 1367-4811
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Popis
Shrnutí: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. Availability: MedScan is available for commercial licensing from Ariadne Genomics, Inc.
Bibliografia:Contact: nikolai@ariadnegenomics.com
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ISSN:1367-4803
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btg207