Chronic Obstructive Pulmonary Disease (Copd) Prediction Using Machine Learning

Abstract

In this Advanced era Chronic Inflammatory lung disease is increasing day by day. Chronic Obstructive Pulmonary Disease (COPD) is one of them which is highly conventional disease characterized by obstructed air flow from the lung. According to research, COPD occurs in people over the age of 40. The amount of affecting rates is getting increased for smoking rates, pollution, industrial pollution in the developed World. Though we believe in advance Era but we don't have sufficient awareness about COPD. People also don't know the level of COPD are currently affected. As like other disease COPD also has some state of condition like (mild, moderate, severe, very severe). Here we implement machine learning algorithm which build a model. Model predict a level of Chronic Obstructive pulmonary Disease Level. We Learn our model with the symptom’s basis data. Our system predicts the disease if have then it will give the level of the disease analyzing the symptoms provide by the user as input. Prediction of chronic obstructive pulmonary disease is done by implementing Machine Learning Algorithms such as Logistic Regression, Decision Tree Classifier, K-Nearest Neighbor, Naïve Bayes. Therefore, we can say our model and data set have more information than past utilize. Finally, our model has standard functional testing.