Prediction of Swine Flu (H1N1) Virus Using Data Mining and Convolutional Neural Network Techniques

Abstract

Swine flu is a transmitting virus which causes risk to health of humans, and it damages all functioning systems and gives rise to bare high-risk symptoms that which are harmful to community where effected person lives and works. Data mining plays a significant role in predicting diseases. The database report of medical patient is not more efficient; currently, we made an endeavor to detect the most widely spread disease all over the world named swine flu. Swine flu is a respiratory disease which has numeral number of tests and must be requisite from the patient for detecting a disease. Advanced data mining techniques give us help to remedy this situation. This paper describes about a prototype using data mining techniques, namely Naive Bayesian classifier. The data mining is an emerging research trend which helps in finding accurate solutions in many fields. This paper highlights the various data mining techniques and convolutional neural network techniques used for predicting swine flu diseases.