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Binary acronym disambiguation in clinical notes from electronic health records with an application in computational phenotyping

  • Published:2022-06 Issue: Volume:162 Page:104753
  • ISSN:1386-5056
  • Container-title:International Journal of Medical Informatics
  • language:en
  • Short-container-title:International Journal of Medical Informatics

Author:

Link Nicholas B.,Huang Sicong,Cai Tianrun,Sun Jiehuan,Dahal Kumar,Costa Lauren,Cho Kelly,Liao Katherine,Cai Tianxi,Hong Chuan

Publisher

Elsevier BV

Subject

Health Informatics

Reference53 articles.

1. S. Yu, T. Cai, NILE: Fast Natural Language Processing for Electronic Health Records, arXiv preprint arXiv:13116063. 2013.

2. Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications;Savova;J. Am. Med. Inform. Assoc.,2010

3. A suite of natural language processing tools developed for the I2B2 project;Goryachev;AMIA Annu. Symp. Proc.,2006

4. Integrated cTAKES for Concept Mention Detection and Normalization;Liu;CLEF (Working Notes),2013

5. Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program;Aronson;Proc. AMIA Symp.,2001

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4. An Initial Study of Abbreviation Disambiguation in Vietnamese Clinical Texts;2024 18th International Conference on Ubiquitous Information Management and Communication (IMCOM);2024-01-03

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