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Using natural language processing to extract health-related causality from Twitter messages ...
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Extracting health-related causality from twitter messages using natural language processing
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A Preliminary Study of Clinical Concept Detection Using Syntactic Relations
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Abstract:
Concept detection is an integral step in natural language processing (NLP) applications in the clinical domain. Clinical concepts are detailed (e.g., “pain in left/right upper/lower arm/leg”) and expressed in diverse phrase types (e.g., noun, verb, adjective, or prepositional phrase). There are rich terminological resources in the clinical domain that include many concept synonyms. Even with these resources, concept detection remains challenging due to discontinuous and/or permuted phrase occurrences. To overcome this challenge, we investigated an approach to exploiting syntactic information. Syntactic patterns of concept phrases were mined from continuous, non-permuted forms of synonyms, and these patterns were used to detect discontinuous and/or permuted concept phrases. Experiments on 790 de-identified clinical notes showed that the proposed approach can potentially boost a recall of concept detection. Meanwhile, challenges and limitations were noticed. In this paper, we report and discuss our preliminary analysis and finding.
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Keyword:
Articles
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URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371372/
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Applying Semantic-based Probabilistic Context-Free Grammar to Medical Language Processing – A Preliminary Study on Parsing Medication Sentences
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Recognizing Medication related Entities in Hospital Discharge Summaries using Support Vector Machine
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BioCaster: detecting public health rumors with a Web-based text mining system
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BioCaster: detecting public health rumors with a Web-based text mining system
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