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 …

Osteoporosis is a skeletal disease that is commonly seen in older people but often
neglected due to its silent nature. To overcome the issue of osteoporosis in men and …

Counterfactual explanations (CEs) aim to enhance the interpretability of machine learning
models by illustrating how alterations in input features would affect the resulting predictions …

Vertebral fractures are a consequence of osteoporosis, with significant health implications
for affected patients. Unfortunately, grading their severity using CT exams is hard and …

Automatically labeling and segmenting vertebrae in 3D CT images compose a complex
multi-task problem. Current methods progressively conduct vertebra labeling and semantic …

Background: Degenerative spinal pathologies are highly prevalent among the elderly
population. Timely diagnosis of osteoporotic fractures and other degenerative deformities …

As one of fundamental ways to interpret spine images, detection of vertebral landmarks is an
informative prerequisite for further diagnosis and management of spine disorders such as …

Automatic vertebral osteophyte recognition in Digital Radiography is of great importance for
the early prediction of degenerative disease but is still a challenge because of the tiny size …

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