International journal of advanced smart convergence

The Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회)
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Disease risk prediction system using correlated health indexes

  • Kim, Yoonjung (Laboratory of Computational Biology & Bioinformatics, Institute of Public Health and Environment, Graduate School of Public Health, Seoul National University) ;
  • Son, Hyeon Seok (SNU Bioinformatics Institute, Interdisciplinary Graduate Program in Bioinformatics, College of Natural Science, Seoul National University) ;
  • Kim, Hayeon (Department of Biomedical Laboratory Science, Kyungdong University)
  • Received : 2018.08.31
  • Accepted : 2018.09.11
  • Published : 2018.12.31
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Abstract

With developments in science and technology and improvement in living standards, human life expectancy is steadily increasing worldwide. For effective healthcare, it is necessary to check health conditions according to individuals' behavior and acquire prior knowledge on possible diseases. In this study, we classified the diseases that are major causes of death in Korea by referring to data provided by the Korea National Health and Nutrition Examination Survey. We selected indexes that could be used as indicators of major diseases and created the LCBB-SC. In the LCBB-SC, the data are systematically subdivided into related fields to provide integrated data related to each disease and to provide an infrastructure that can be used by researchers. In addition, by developing a web interface allowing for self-symptom assessments, this resource will be beneficial to people who want to check their own health condition using a list of diseases that might be caused by their behaviors.

Keywords

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Figure 1. Workflow of the research

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Figure 2. The Lab of Computer Biology and Bioinformatics - Symptom Checker (LCBB-SC)

Table 1. System development environment

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Table 2. Type and number of data used for system construction

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Table 3. Multiple layer perceptron result for chronic disease (10-folds)

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