Objective To assess the methodological quality of studies on prediction models developed
using machine learning techniques across all medical specialties. Design Systematic …

Bone diseases are common and can result in various musculoskeletal conditions (MC). An
estimated 1.71 billion patients suffer from musculoskeletal problems worldwide. Apart from …

Radiomics and machine learning–based methods offer exciting opportunities for improving
diagnostic performance and efficiency in musculoskeletal radiology for various tasks …

Osteoporosis and its clinical consequence, bone fracture, is a multifactorial disease that has
been the object of extensive research. Recent advances in machine learning (ML) have …

Osteoporosis, a metabolic bone disease characterized by low bone mineral density and
deterioration of bone microarchitecture, has led to a high risk of fatal osteoporotic fractures …

Osteoporosis care has evolved markedly over the last 50 years, such that there are now an
established clinical definition, validated methods of fracture risk assessment, and a range of …

BACKGROUND AND PURPOSE: Multidetector CT has emerged as the standard of care
imaging technique to evaluate cervical spine trauma. Our aim was to evaluate the …

Purpose The field of artificial intelligence is ever growing and the applications of machine
learning in spine care are continuously advancing. Given the advent of the intelligence …

Background Since image-based fracture prediction models using deep learning are lacking,
we aimed to develop an X-ray-based fracture prediction model using deep learning with …

Spinal maladies are among the most common causes of pain and disability worldwide.
Imaging represents an important diagnostic procedure in spinal care. Imaging investigations …