Artificial intelligence (AI) and its recent increasing healthcare integration has created both
new opportunities and challenges in the practice of radiology and medical imaging. Recent …

Spinal injuries, including cervical and thoracolumbar fractures, continue to be a major public
health concern. Recent advancements in machine learning and deep learning technologies …

An abundance of medical data and enhanced computational power have led to a surge in
artificial intelligence (AI) applications. Published studies involving AI in bone and …

Purpose We developed and tested a neural network for automated detection and stability
analysis of vertebral body fractures on computed tomography (CT). Materials and Methods …

Artificial Intelligence (AI), encompassing Machine Learning and Deep Learning, has
increasingly been applied to fracture detection using diverse imaging modalities and data …

Objectives To review studies on deep learning (DL) models for classification, detection and
segmentation of rib fractures in CT data, to determine their risk of bias (ROB), and to analyse …

Pelvic fractures pose significant challenges in medical diagnosis due to the complex
structure of the pelvic bones. Timely diagnosis of pelvic fractures is critical to reduce …

Objective. In the context of primary in-hospital trauma management timely reading of
computed tomography (CT) images is critical. However, assessment of the spine is time …

Pelvic ring disruptions result from blunt injury mechanisms and are potentially lethal mainly
due to associated injuries and massive pelvic hemorrhage. The severity of pelvic fractures in …

Purpose To evaluate the diagnostic accuracy of machine learning (ML) in detecting vertebral
fractures, considering varying fracture classifications, patient populations, and imaging …