Medical Concept Normalization for Online User-Generated Texts

Kathy Lee, Sadid A. Hasan, Oladimeji Farri, Alok Choudhary, Ankit Agrawal

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

7 Scopus citations

Abstract

Social media has become an important tool for sharing content in the last decade. People often talk about their experiences and opinions on different health-related issues e.g. they write reviews on medications, describe symptoms and ask informal questions about various health concerns. Due to the colloquial nature of the languages used in the social media, it is often difficult for an automated system to accurately interpret them for appropriate clinical understanding. To address this challenge, this paper proposes a novel approach for medical concept normalization of user-generated texts to map a health condition described in the colloquial language to a medical concept defined in standard clinical terminologies. We use multiple deep learning architectures such as convolutional neural networks (CNN) and recurrent neural networks (RNN) with input word embeddings trained on various clinical domain-specific knowledge sources. Extensive experiments on two benchmark datasets demonstrate that the proposed models can achieve up to 21.28% accuracy improvements over the existing models when we use the combination of all knowledge sources to learn neural embeddings.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE International Conference on Healthcare Informatics, ICHI 2017
EditorsMollie Cummins, Julio Facelli, Gerrit Meixner, Christophe Giraud-Carrier, Hiroshi Nakajima
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages462-469
Number of pages8
ISBN (Electronic)9781509048816
DOIs
StatePublished - Sep 8 2017
Event5th IEEE International Conference on Healthcare Informatics, ICHI 2017 - Park City, United States
Duration: Aug 23 2017Aug 26 2017

Publication series

NameProceedings - 2017 IEEE International Conference on Healthcare Informatics, ICHI 2017

Other

Other5th IEEE International Conference on Healthcare Informatics, ICHI 2017
CountryUnited States
CityPark City
Period8/23/178/26/17

Keywords

  • Deep learning
  • Medical concept normalization
  • Social media

ASJC Scopus subject areas

  • Health Informatics

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  • Cite this

    Lee, K., Hasan, S. A., Farri, O., Choudhary, A., & Agrawal, A. (2017). Medical Concept Normalization for Online User-Generated Texts. In M. Cummins, J. Facelli, G. Meixner, C. Giraud-Carrier, & H. Nakajima (Eds.), Proceedings - 2017 IEEE International Conference on Healthcare Informatics, ICHI 2017 (pp. 462-469). [8031195] (Proceedings - 2017 IEEE International Conference on Healthcare Informatics, ICHI 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICHI.2017.59