Deep learning could help medical professionals diagnose skin diseases

Researchers in Korea have developed a convolutional neural network (CNN) architecture capable of aiding specialists in the diagnosis of 134 skin disorders. Their algorithm can also predict treatment options. With the assistance of this method, the team found that the diagnostic accuracy of dermatologists as well as the general public was significantly improved. The neural network was trained with 220,680 images of 174 disorders and validated using Edinburgh (1,300 images; 10 disorders) and Seoul National University datasets (2,201 images; 134 disorders). The datasets consisted of images of Asians and Caucasians.