Transfer Learning-Based Comparative Analysis of Lung Disease Prediction

The factors such as contaminated air, infection, and smoking, the lung disease issue have become the most prevalent health concerns in the entire globe for people of all ages. The most predominant forms of respiratory disease are tuberculosis, pneumonia, and COVID-19. Several research projects have been conducted using Artificial Intelligence-based technologies to enhance the precision and accuracy of such disease. The typical tasks are to forecast and classify lung disease using Chest X-ray, MRI images, and CT with DL, and TL models. The primary objective of this work is to provide a relative study of VGG-16, ResNet-50, and DenseNet201 CNN-based TL techniques and to recommend which image classification algorithm is best for forecasting and classifying lung disease.