Performance of a Natural Language Processing Method to Extract Stone Composition From the Electronic Health Record.

Journal: Urology

Published Date: Jul 13, 2019

Abstract

OBJECTIVES: To demonstrate the utility of a natural language processing (NLP) algorithm for mining kidney stone composition in a large-scale electronic health records (EHR) repository.

Authors

Cosmin A Bejan

Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN.
Daniel J Lee
Yaomin Xu

Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN; Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN.
Ryan S Hsi

Department of Urology, Vanderbilt University Medical Center, Nashville, TN. Electronic address: ryan.hsi@vanderbilt.edu.

Keywords

Case-Control Studies Electronic Health Records Female Humans Kidney Calculi Male Natural Language Processing

External Resources

View on PubMed Access via DOI PubMed (31310771)

Performance of a Natural Language Processing Method to Extract Stone Composition From the Electronic Health Record.

Abstract

Authors

Keywords

External Resources

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