Integrating Automated Biomedical Lexicon Creation for Valley Fever Diagnosis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Named Entity Recognition (NER) is an important task in biomedical NLP which identifies and categorizes entities in biomedical text. We currently focus on a rule-based approach for NER to identify the diagnostic criteria of valley fever in the free text of electronic health records (EHRs), since no training data exist for machine learning. To aid the manual pattern defining process of the rule-based approach, we propose a graph-based lexicon expansion method. We used different word embedding models to create a lexicon graph and expanded the lexicons by conducting different graph search methods.

Original languageEnglish (US)
Title of host publicationProceedings - 2021 IEEE/ACM Conference on Connected Health
Subtitle of host publicationApplications, Systems and Engineering Technologies, CHASE 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages111-112
Number of pages2
ISBN (Electronic)9781665439657
DOIs
StatePublished - 2021
Event6th IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2021 - Washington, United States
Duration: Dec 16 2021Dec 18 2021

Publication series

NameProceedings - 2021 IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2021

Conference

Conference6th IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2021
Country/TerritoryUnited States
CityWashington
Period12/16/2112/18/21

Keywords

  • EHR
  • electronic health records
  • graph search
  • lexicon
  • lexicon expansion
  • lexicon extension
  • valley fever
  • word embeddings

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Information Systems and Management
  • Medicine (miscellaneous)
  • Health Informatics
  • Health(social science)

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