One of the goals of the proposed research is to extract knowledge summaries automatically to assist physicians in making the best patient-care decisions. Specifically, this involves information retrieval, information extraction and multi-document summarization. I have significant expertise in all these individual components needed for the system. During the last few years, I have built and investigated several text mining tools. Some of the tools designed and developed by me are BioSimplify (system that simplifies biomedical sentences), NEMO (system that extracts and normalizes institution names from PubMed abstracts) and SimFind (system that extracts biomedical concepts using distributional similarity kernels). The current application builds logically on my prior work. In addition, I was the research lead for the terminology indexing of clinical documents Enterprise Data trust (Mayo Clinic’s clinical datawarehouse). We will be contributing to the retrieval of relevant CCDs from clinical documents for the proposed experiments.
|Effective start/end date
|10/1/13 → 3/31/16
- University of Utah (10028048-02 // R01LM011416)
- National Library of Medicine (10028048-02 // R01LM011416)
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