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Constructing and Visualizing Models using Mime-based Machine-learning Framework
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Infectious disease outbreak prediction using media articles with machine learning models.

Juhyeon Kim1,2, Insung Ahn3,4

  • 1Department of Data-Centric Problem Solving Research, Korea Institute of Science and Technology Information, Yuseong-gu, Daejeon, Korea.

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Summary
This summary is machine-generated.

This study explored using internet news data to predict emerging infectious diseases. Machine learning models successfully detected disease outbreak patterns from news articles, offering a novel approach to public health surveillance.

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Area of Science:

  • Epidemiology
  • Public Health Surveillance
  • Computational Biology

Background:

  • Emerging infectious diseases pose significant threats to global health and economies.
  • Predicting disease outbreaks and developing countermeasures is crucial for preparedness.
  • Traditional data collection for emerging diseases is challenging due to rapid, sporadic spread.

Purpose of the Study:

  • To investigate the feasibility of using internet news data for early detection of emerging infectious diseases.
  • To evaluate the effectiveness of machine learning models in identifying disease outbreak patterns from news articles.

Main Methods:

  • Collected infectious disease-related internet articles from Medisys (January-December 2019).
  • Employed machine learning algorithms: Support Vector Machine (SVM), Semi-supervised Learning (SSL), and Deep Neural Network (DNN).
  • Analyzed news data to detect patterns indicative of emerging infectious disease outbreaks.

Main Results:

  • News article data can be utilized to detect patterns of newly emerging infectious diseases.
  • Machine learning models demonstrated potential in identifying disease outbreak signals from web articles.
  • The study confirmed the value of online news as a data source for infectious disease surveillance.

Conclusions:

  • Internet news articles serve as a valuable, rapidly reflecting data source for monitoring public health issues.
  • Machine learning approaches, applied to news data, show promise for early detection of infectious disease outbreaks.
  • This method offers a novel strategy for enhancing global infectious disease surveillance systems.