Parallel Training Using a CNN-DNN Architecture for Accelerated Development of Diagnostic Models

Artificial intelligence has shown promise in assisting radiologists in imaging-based diagnosis across a wide range of diseases. Efficient training of large deep learning models is essential to cope with extremely large data sets or dynamically growing disease data, like in a pandemic like situation.