Stanford researchers trained a convolutional neural network on a data set of 40,895 images from 14,982 studies. The paper documents how the algorithm detected abnormalities (like fractures, or bone degeneration) better than radiologists in finger and wrist radiographs. However, radiologists were still better at spotting issues in elbows, forearms, hands, upper arms, and shoulders.