MedScan, a natural language processing engine for MEDLINE abstracts | Zendy

Svetlaovichkova | Zendy; Sergei Egorov | Zendy; Nikolai Daraselia | Zendy

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MedScan, a natural language processing engine for MEDLINE abstracts

Author(s) -

Svetlaovichkova,

Sergei Egorov,

Nikolai Daraselia

Publication year - 2003

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btg207

Subject(s) - computer science , natural language processing , lexicon , information extraction , parsing , ambiguity , domain (mathematical analysis) , context (archaeology) , information retrieval , artificial intelligence , sentence , unified medical language system , natural language , set (abstract data type) , meaning (existential) , biomedical text mining , text mining , programming language , mathematical analysis , paleontology , mathematics , biology , psychology , psychotherapist

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.

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