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The Study of Patient Prediction Models on Flu, Pneumonia and HFMD Using Big Data  

Yu, Jong-Pil (세종대학교 경영학과)
Lee, Byung-Uk (세종대학교 경영학과)
Lee, Cha-min (세종대학교 경영학과)
Lee, Ji-Eun (세종대학교 경영학과)
Kim, Min-sung (세종대학교 경영학과)
Hwang, Jae-won (세종대학교 경영학과)
Publication Information
The Journal of Bigdata / v.3, no.1, 2018 , pp. 55-62 More about this Journal
Abstract
In this study, we have developed a model for predicting the number of patients (flu, pneumonia, and outbreak) using Big Data, which has been mainly performed overseas. Existing patient number system by government adopt procedures that collects the actual number and percentage of patients from several big hospital. However, prediction model in this study was developed combing a real-time collection of disease-related words and various other climate data provided in real time. Also, prediction number of patients were counted by machine learning algorithm method. The advantage of this model is that if the epidemic spreads rapidly, the propagation rate can be grasped in real time. Also, we used a variety types of data to complement the failures in Google Flu Trends.
Keywords
Big Data; Flu; Pneumonia; Outbreak; Real-Time Predictions;
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