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DiTeX: Disease-related topic extraction system through internet-based sources.

Jungwon Yoon1, Jong Wook Kim1, Beakcheol Jang1

  • 1Department of Computer Science, Sangmyung University, Seoul, South Korea.

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|August 4, 2018
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Summary
This summary is machine-generated.

DiTeX is a novel system for automated disease-related topic extraction from online sources. It uses Natural Language Processing and a unique ranking algorithm to identify and present timely public health information more effectively than traditional methods.

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Area of Science:

  • Public Health Informatics
  • Computational Linguistics
  • Data Science

Background:

  • National disease surveillance systems face delays in disseminating outbreak information.
  • Internet sources like news and social media offer real-time data but contain noise.
  • Existing methods struggle to efficiently extract critical disease-related topics from diverse online information.

Purpose of the Study:

  • To develop DiTeX, an automated web-based system for extracting and presenting disease-related topics and trends.
  • To address the challenge of noisy data in online sources for public health surveillance.
  • To evaluate the performance and effectiveness of DiTeX's topic extraction and ranking algorithms.

Main Methods:

  • Utilized Natural Language Processing (NLP) and a proprietary ranking algorithm for topic extraction.
  • Developed a web-based system with front-end and back-end architecture for data collection and processing.
  • Collected Internet-based data using search keywords and applied the ranking algorithm to evaluate topic importance.

Main Results:

  • DiTeX demonstrated superior topic extraction rates compared to other ranking algorithms.
  • The system successfully extracts and summarizes daily disease-related topics from web sources.
  • Real-world incident analysis validated the performance and effectiveness of DiTeX.

Conclusions:

  • DiTeX is the first automated web-based real-time service for extracting disease-related topics from online data.
  • The system offers a significant improvement over traditional surveillance methods for timely public health information.
  • DiTeX provides a valuable tool for monitoring disease trends and related data through web sources.