1. An entity tagger for recognizing acquired genomic variations in cancer literature.
- Author
-
McDonald RT, Winters RS, Mandel M, Jin Y, White PS, and Pereira F
- Subjects
- Artificial Intelligence, Database Management Systems, Genetic Predisposition to Disease genetics, Genetic Variation, Genome, Pattern Recognition, Automated methods, Software, User-Computer Interface, Vocabulary, Controlled, Abstracting and Indexing methods, Algorithms, Databases, Bibliographic, Information Storage and Retrieval methods, Natural Language Processing, Neoplasms genetics, Periodicals as Topic
- Abstract
VTag is an application for identifying the type, genomic location and genomic state-change of acquired genomic aberrations described in text. The application uses a machine learning technique called conditional random fields. VTag was tested with 345 training and 200 evaluation documents pertaining to cancer genetics. Our experiments resulted in 0.8541 precision, 0.7870 recall and 0.8192 F-measure on the evaluation set.
- Published
- 2004
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