FORECASTING PHILIPPINES PNEUMONIA MORBIDITY UTILIZING ARTIFICIAL INTELLIGENCE

Abstract

In Philippines, pneumonia remains to be on the top ten (10) leading the cause of both morbidity and mortality during many decades (Department of Health). According to the health care providers, there is a need for us to look into this alarming health scenario. One important way is to forecast the pneumonia cases based on the actual data for the last twenty (20) years. The prediction can be a good basis for the health sector to find a more effective way to manage pneumonia cases in the country. To forecast the future yearly cases of pneumonia, artificial intelligence forecasting methos is used. A time series (20-year) data from 1993-2013 was utilized in data mining using minitab and Eureqa software. The trend component of forecasting pneumonia morbidity shows a flat line model indicating that pneumonia morbidity cases will remain on the same level every year of around 718,144 cases if the current health care system continues the current pneumonia management approaches. The correction factor, however, tells us that there are higher frequencies “up” and “down” pulling movement because of the presence of the sine functions. This implies that if a significant reduction of pneumonia cases is envisioned, then a planned and focused pneumonia management program shall be created and implemented.