Injury
-
In recent years, the scientific community focused on developing Computer-Aided Diagnosis (CAD) tools that could improve clinicians' bone fractures diagnosis, primarily based on Convolutional Neural Networks (CNNs). However, the discerning accuracy of fractures' subtypes was far from optimal. The aim of the study was 1) to evaluate a new CAD system based on Vision Transformers (ViT), a very recent and powerful deep learning technique, and 2) to assess whether clinicians' diagnostic accuracy could be improved using this system. ⋯ This paper showed the potential of Vision Transformers in bone fracture classification. For the first time, good results were obtained in sub-fractures classification, outperforming the state of the art. Accordingly, the assisted diagnosis yielded the best results, proving the effectiveness of collaborative work between neural networks and clinicians.
-
Comment Letter Randomized Controlled Trial
Intramedullary nail versus bridge plate in open tibial fractures - randomized clinical trial.