Chinese chief complaint classification for syndromic surveillance

  • Authors:

  • Hsin-Min Lu;Chwan-Chuen King;Tsung-Shu Wu;Fuh-Yuan Shih;Jin-Yi Hsiao;Daniel Zeng;Hsinchun Chen

  • Affiliations:

  • Management Information Systems Department, Eller College of Management, University of Arizona, Tucson, Arizona;Graduate Institute of Epidemiology, National Taiwan University, Taipei, Taiwan;Graduate Institute of Epidemiology, National Taiwan University, Taipei, Taiwan;Department of Emergency Medicine, National Taiwan University Hospital, Taipei, Taiwan;Graduate Institute of Epidemiology, National Taiwan University, Taipei, Taiwan;Management Information Systems Department, Eller College of Management, University of Arizona, Tucson, Arizona;Management Information Systems Department, Eller College of Management, University of Arizona, Tucson, Arizona

  • Venue:
  • BioSurveillance'07 Proceedings of the 2nd NSF conference on Intelligence and security informatics: BioSurveillance
  • Year:
  • 2007

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Abstract

There is a critical need for the development of chief complaint (CC) classification systems capable of processing non-English CCs as syndromic surveillance is being increasingly practiced around the world. In this paper, we report on an ongoing effort to develop a Chinese CC classification system based on the analysis of Chinese CCs collected from hospitals in Taiwan. We found that Chinese CCs contain important symptom-related information and provide a valid source of information for syndromic surveillance. Our technical approach consists of two key steps: (a) mapping Chinese CCs to English CCs using a mutual information-based mapping method, and (b) reusing existing English CC classification systems to process translated Chinese CCs. We demonstrate the effectiveness of this proposed approach through a preliminary evaluation study using a real-world dataset.