Understanding Transfer Learning For Medical Applications

From interpreting chest x-rays to identifying eye diseases, the domain of transfer learning has found its significance in a variety of standard medical tasks. Therefore, it is extremely important to understand the commonly held assumptions, challenges and other solutions within the realms of transfer learning. In transfer learning, the neural network is trained in two stages:  Pre-training: The network is generally trained on a large-scale benchmark dataset representing a wide range of categoriesFine-tuning: Pre-trained network is further trained on the specific target task of interest, which may have fewer labelled examples than the pre-training dataset.  What Are The Challenges? In spite of being widely popular there are still few pressing questions botherin