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Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
Published on: February 23, 2019
Exploring relations among semantic groups: a comparison of concept co-occurrence in biomedical sources
Sasikiran Kandula1, Qing Zeng-Treitler
1Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA.
Abstract:
It has been observed and reported that the patient's mental model of the medical domain is different from that of a health professional and this difference is one of the primary obstacle in the effective communication of health information to patients. In this study, to better understand these mental models, we explored the relations among different semantic groups of concepts in consumer- and professional-generated health content by analyzing concept co-occurrence information in three biomedical sources. We found significant differences in the prevalence of the semantic groups and the strength of co-occurrences between semantic groups in the three sources. The co-occurrence defined by consumers differs from that defined by professionals. The two professional sources have noticeable differences with each other as well. We believe that addressing these differences can help us generate more informative and consumer-friendly health content as well as develop better consumer health informatics applications.
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