A computational semantics system for detecting drug reactions and patient outcomes in personal health messages
Jiang, Yunliang
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https://hdl.handle.net/2142/24194
Description
Title
A computational semantics system for detecting drug reactions and patient outcomes in personal health messages
Author(s)
Jiang, Yunliang
Issue Date
2011-05-25T14:51:43Z
Director of Research (if dissertation) or Advisor (if thesis)
Schatz, Bruce R.
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
drug-based
outcome
filtering
clustering
summarizing
Abstract
Case studies are a standard approach to medicine. A physician needs the outcomes of a drug, situationally relevant to a particular patient. We propose a system for patient outcomes utilizing computational semantics, which effectively digests message groups. Filtering identifies personal comments, by eliminating useless messages. Clustering groups similar topics from different messages, by statistical overlap with specified terms. Summarizing labels the clusters so content can be quickly digested. We implemented a prototype system with these functions for mining health messages. Our methods do not require extensive training or dictionaries, while enabling users to specify custom topics for digesting. This system has been tested with sample messages from our unique dataset from Yahoo! Groups, containing 12M personal messages from 27K public groups in Health and Wellness. Evaluated results show high quality of
labeled clustering, promising an effective automatic system for discovering useful information
across large volumes of health information.
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