Constructing the First Convolutional Neural Network for Determining Damaged Bones and Normal Bones in X-Ray Images - Mishra, Akshansh; Datta, Priyankan (International Journal of Computer Sciences and Engineering, 2019)
Deep learning technology applied to medical imaging may become the most disruptive technology radiology has seen since the advent of digital imaging. Most researchers believe that within next 15 years, deep learning based applications will take over human and not only most of the diagnosis will be performed by intelligent machines but will also help to predict disease, prescribe medicine and guide in treatment. In this case study, Convolutional Neural Network (CNN) has been constructed to determine the nature of bones i.e. whether it is broken or intact. Python is used as a basic language for coding purpose. It can be seen that after 50 epochs the validation accuracy is 96.39 %, it shows the ability of the model to generalize to new data.