NanoChest-Net: A Simple Convolutional Network for Radiological Studies Classification.

ABSTRACT: The new coronavirus disease (COVID-19), pneumonia, tuberculosis, and breast cancer have one thing in common: these diseases can be diagnosed using radiological studies such as X-rays images. With radiological studies and technology, computer-aided diagnosis (CAD) results in a very useful technique to analyze and detect abnormalities using the images generated by X-ray machines. Some deep-learning techniques such as a convolutional neural network (CNN) can help physicians to obtain an effective pre-diagnosis. However, popular CNNs are enormous models and need a huge amount of data to obtain good results. In this paper, we introduce NanoChest-net, which is a small but effective CNN model that can be used to classify among different diseases using images from radiological studies. NanoChest-n

SUBMITTER: Lujan-Garcia JE 

PROVIDER: S-EPMC8145173 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature