Experimenting with Clojure on Extracting Medication Information from Clinical Narratives
Pages 119 - 122
Abstract
The path towards electronic healthcare records is nonetheless not free of challenges including the large amount of clinical information buried in narrative content. Medication information is one of the most important types of clinical data in electronic healthcare records. It is critical for healthcare safety and quality, as well as for clinical research to have such information identified correctly. Natural language processing (NLP) is essential to phenotyping the medication data. However, recognizing medication patterns based on general NLP techniques fail short to identify such patterns with great accuracy even if they were trained with relevant clinical treebanks or corpuses. This article describes how Clojure and OpenNLP API can be used to identify medication patterns and train the clinical narrative chuncker to accurately identify given medication patterns.
References
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Index Terms
- Experimenting with Clojure on Extracting Medication Information from Clinical Narratives
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Published In
October 2018
217 pages
ISBN:9781450365192
DOI:10.1145/3289430
Copyright © 2018 ACM.
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- Deakin University
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 24 October 2018
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BDIOT 2018
BDIOT 2018: 2018 2nd International Conference on Big Data and Internet of Things
October 24 - 26, 2018
Beijing, China
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Overall Acceptance Rate 75 of 136 submissions, 55%
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