A statistical medical summary translation system

  • Authors:

  • Han-Bin Chen;Hen-Hsen Huang;Ching-Ting Tan;Jengwei Tjiu;Hsin-Hsi Chen

  • Affiliations:

  • National Taiwan University, Taipei, Taiwan Roc;National Taiwan University, Taipei, Taiwan Roc;National Taiwan University Hospital, Taipei, Taiwan Roc;National Taiwan University Hospital, Taipei, Taiwan Roc;National Taiwan University, Taipei, Taiwan Roc

  • Venue:
  • Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
  • Year:
  • 2012

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Abstract

In a hospital, a medical summary is indispensable for both a clinician and a patient. However, it is written in English in some non-English native countries and becomes a barrier for a patient to read. In this paper we propose a framework for rapid acquisition of bilingual medical summaries using machine translation (MT) techniques. We describe a medical summary corpus and some terminological databases prepared for the framework. We then touch on the challenging issues of MT adapted from generic to specific domains, and propose a pattern translation scheme to achieve domain adaptation based on a background statistical MT system. We identify the significant patterns to capture the specific writing styles in a medical summary. The patterns are then translated with the involvements of doctors. Our major concern is to reduce the cost of translation and better allocate the efforts made by the domain experts. The experimental results show the proposed methods are effective in terms of the significance and diversity of the patterns. The approaches to integrate the mined patterns into background MT are also discussed.