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Abstract
Grant Number: 5R01LM007050-05 Project Title: Adaptive Information Monitoring and Extraction
PI Information: Name Title CRAVEN, MARK W. craven@biostat.wisc.edu ASSISTANT PROFESSOR Abstract: DESCRIPTION (provided by applicant): It is now widely recognized that there is a great need for more powerful automated methods to assist biomedical scientists in filtering, querying, and extracting information from the scientific literature. Building on our past research accomplishments in biomedical text mining, we plan to develop new algorithms and software systems that will significantly improve the ability of biomedical researchers to exploit the scientific literature. In particular, we plan to develop, evaluate and field systems that (1) aid in annotating high-throughput experiments by extracting and organizing information from text sources, and (2) assist genome database curators by identifying relevant articles and predicting appropriate ontology codes for specific query genes and proteins. In support of these systems, we plan to develop novel machine-learning based text-mining algorithms for training on coarsely labeled data, and inducing models of relationships among specific types of entities expressed in natural language.
Public Health Relevance:
This Public Health Relevance is not available.Thesaurus Terms:
computer human interaction, computer program /software, computer system design /evaluation, information retrieval, vocabulary development for information system
information system, method development, online computer
human data
Institution: UNIVERSITY OF WISCONSIN MADISON 21 N. Park Street, Suite 6401 MADISON, WI 537151218 Fiscal Year: 2008 Department: BIOSTATISTICS & MED INFORMATICS Project Start: 29-SEP-2000 Project End: 30-JUN-2010 ICD: NATIONAL LIBRARY OF MEDICINE IRG: BLR