Diagnostic accuracy of a deep learning model using YOLOv5 for detecting developmental dysplasia of the hip on radiography images

We developed deep learning models for detecting DDH using hip radiography images in the AP view. To the best of our knowledge, this is the first study to achieve this using YOLOv5 and SSD. In addition, using the transfer learning technique, a good model could be constructed with a relatively small dataset. The benefit of using an object detection model rather than a classification model is the ability of the object detection model to evaluate both hips simultaneously without image processing, and that the image outcomes are easy to understand.

The disadvantage of YOLOv5, in general, is that…