https://scholars.lib.ntu.edu.tw/handle/123456789/534358
Title: | Multilingual chief complaint classification for syndromic surveillance: An experiment with Chinese chief complaints | Authors: | Lu H.-M. Chen H. Zeng D. King C.-C. FUH-YUAN SHIH Wu T.-S. Hsiao J.-Y. |
Issue Date: | 2009 | Journal Volume: | 78 | Journal Issue: | 5 | Start page/Pages: | 308-320 | Source: | International Journal of Medical Informatics | Abstract: | Purpose: Syndromic surveillance is aimed at early detection of disease outbreaks. An important data source for syndromic surveillance is free-text chief complaints (CCs), which may be recorded in different languages. For automated syndromic surveillance, CCs must be classified into predefined syndromic categories to facilitate subsequent data aggregation and analysis. Despite the fact that syndromic surveillance is largely an international effort, existing CC classification systems do not provide adequate support for processing CCs recorded in non-English languages. This paper reports a multilingual CC classification effort, focusing on CCs recorded in Chinese. Methods: We propose a novel Chinese CC classification system leveraging a Chinese-English translation module and an existing English CC classification approach. A set of 470 Chinese key phrases was extracted from about one million Chinese CC records using statistical methods. Based on the extracted key phrases, the system translates Chinese text into English and classifies the translated CCs to syndromic categories using an existing English CC classification system. Results: Compared to alternative approaches using a bilingual dictionary and a general-purpose machine translation system, our approach performs significantly better in terms of positive predictive value (PPV or precision), sensitivity (recall), specificity, and F measure (the harmonic mean of PPV and sensitivity), based on a computational experiment using real-world CC records. Conclusions: Our design provides satisfactory performance in classifying Chinese CCs into syndromic categories for public health surveillance. The overall design of our system also points out a potentially fruitful direction for multilingual CC systems that need to handle languages beyond English and Chinese. ? 2008 Elsevier Ireland Ltd. All rights reserved. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/534358 | ISSN: | 1386-5056 | DOI: | 10.1016/j.ijmedinf.2008.08.004 | SDG/Keyword: | Communicable disease control; Medical records; Multilingual chief complaint classification; Statistical pattern extraction; Syndromic surveillance; Computer aided language translation; Disease control; Information theory; Linguistics; Security of data; Speech transmission; Translation (languages); Text processing; article; Chinese; data analysis; English as a second language; epidemic; health survey; human; information processing; language; prediction and forecasting; priority journal; public health service; satisfaction; sensitivity analysis; syndromic surveillance; China; Disease Outbreaks; Humans; Language; Reproducibility of Results; Sensitivity and Specificity; Sentinel Surveillance |
Appears in Collections: | 醫學院附設醫院 (臺大醫院) |
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