Prediction Model for Respiratory Diseases Using Machine Learning Algorithms

Abstract

Millions of people around the world have one or many respiratory related illness. Many chronic respiratory diseases like asthma, COPD, pneumonia, respiratory distress etc. are considered to be most significant public health burden. To reduce the mortality rate, it is better to perform early prediction of respiratory disorders and treat them accordingly. To build an efficient prediction model for various types of respiratory diseases, machine learning approaches are used. The proposed methodology build classifier model using supervised learning algorithms like Random forest, decision tree and Multi-layer Perceptron Neural network (MLP-NN) for the detection of different respiratory diseases of ICU admitted patients. It achieves accuracy of nearly 99 percent by various machine learning approaches.

Keywords: respiratory illness, machine learning, asthma, pneumonia, COPD