Recent Trends in the Diagnosis of Pulmonary Disorders using Artificial Intelligence Model

Pulmonary disorder is one of the most common health issues faced by several people. Patients with Pulmonary disorder suffer from several disorders like COPD (Chronic obstructive pulmonary disease), URTI (Upper Respiratory Tract Infection), LRTI (Lower Respiratory Tract Infection) and many more. Traditionally doctors diagnose the disorder using methods like Stethoscopes, CT scans, Chest x-ray, pulmonary function test etc. Now research is progressing to use AI for this. This paper discusses about the different advancements that have happened till now in using Deep learning/Artificial Neural Network to classify the different pulmonary signals, and diagnose the disorder. Different models/ methods like Convolution Neural Network, Recurrent Neural Network, Fourier analysis, Empirical Mode Decomposition, Wavelet Transform, Fast Fourier transform, autoregressive, etc and classifiers like AlexNet, InceptionNet, LeNet-5 etc are discussed with its efficiency, advantage/disadvantage. The paper gives a summary of state-of-the-art technologies available for classification of pulmonary disorders.