Researchers use machine learning to detect fractures in plain radiographs

Machine learning using deep convolutional neural networks (CNNs) can be used to detect fractures in plain radiographs, according to a new study published in Clinical Radiology. A team of researchers from the U.K. taught the CNNs using lateral wrist radiographs performed at a single facility from January 2015 to January 2016. Each image was classified as "fracture" or "no fracture" based on the existing radiology report. The distinction was personally verified by a human specialist before data was used to "train" the CNN. Overall, the area under the receiver operator characteristic curve (AUC) was 0.954, a number the authors said provided a proof of concept.