Swine flu predication using machine learning

Abstract

Disease identification is one of the critical and time-consuming tasks in medical diagnosis system. Machine learning is a foremost technique used to predict and identify the diseases at different levels. It is very spontaneous and on-time process to analyze disease based on clinical and laboratory symptoms with the help of appropriate and initial data, and it also helps us to produce a more efficient diagnosis plan in some diseases. In the past, machine learning helped in predicating many diseases like brain tumor, breast cancer, diabetes diagnosis. Swine flu is one of the diseases which take long procedural time before coming to the conclusion. Here, we try to apply some machine learning algorithms to reduce that time by some margin so that diagnosis of patient is start on time. We have analyzed the current scenario of a medical diagnosis system with different data mining and machine learning techniques and proposed feed-forward neural network to predict the “Swine Flu” disease with some data at initial level.