Paper Title
ARTIFICIAL INTELLIGENCE IN PREDICTION OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE

Abstract
Chronic obstructive lung disease (COPD) is the third leading cause of death in the world and second in India, which has the highest number of cases in the world (55.3 million). Despite the huge and growing burden, COPD remains a badly neglected disease due to incorrect diagnosis, poor management, which leads to recurrent exacerbations, hospitalizations, and death. This article presents the use of artificial intelligence (AI)/machine learning (ML) in COPD diagnosis, severity grading, predicting the risk of exacerbation, and hospital readmissions. The studies with different ML techniques along with conventional statistical analysis are presented. The widely used ML techniques include Support vector machine (SVM), K-Nearest Neighbour (KNN), Random Forest (RF), Probabilistic neural network (PNN), Naive Bayesian, Lasso regression, Machine learning neural network (MLNN) and Boosting, etc. The use of AI is increasing in the field of medical sciences and will definitely continue to grow in the future and it seems to hold promise in the better diagnosis, treatment, and management of COPD. Keywords - Artificial intelligence, machine learning, COPD, diagnosis and prediction.