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http://dx.doi.org/10.9717/kmms.2018.21.2.271

A Prediction of Number of Patients and Risk of Disease in Each Region Based on Pharmaceutical Prescription Data  

Chang, Jeong Hyeon (Dept. of Software, ChungBuk National University)
Kim, Young Jae (Dept. of Software, ChungBuk National University)
Choi, Jong Hyeok (Dept. of Software, ChungBuk National University)
Kim, Chang Su (Dept. of Computer Engineering, PaiChai University)
Aziz, Nasridinov (Dept. of Software, ChungBuk National University)
Publication Information
Journal of Korea Multimedia Society / v.21, no.2, 2018 , pp. 271-280 More about this Journal
Abstract
Recently, big data has been growing rapidly due to the development of IT technology. Especially in the medical field, big data is utilized to provide services such as patient-customized medical care, disease management and disease prediction. In Korea, 'National Health Alarm Service' is provided by National Health Insurance Corporation. However, the prediction model has a problem of short-term prediction within 3 days and unreliability of social data used in prediction model. In order to solve these problems, this paper proposes a disease prediction model using medicine prescription data generated from actual patients. This model predicts the total number of patients and the risk of disease in each region and uses the ARIMA model for long-term predictions.
Keywords
Medicine Prescription Data; Disease Prediction; Region; ARIMA Model; Long-Term Predictions;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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