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

Simple Summary Deep learning has succeeded greatly in medical image-based cancer
diagnosis. To help readers better understand the current research status and ideas, this …

Background Atypical cartilaginous tumour (ACT) and grade II chondrosarcoma (CS2) of long
bones are respectively managed with watchful waiting or curettage and wide resection …

BACKGROUND AND PURPOSE: B-Raf proto-oncogene, serine/threonine kinase (BRAF)
status has important implications for prognosis and therapy of pediatric low-grade gliomas …

Background Clinical management ranges from surveillance or curettage to wide resection
for atypical to higher-grade cartilaginous tumours, respectively. Our aim was to investigate …

In the last two decades, relevant progress has been made in the diagnosis of
musculoskeletal tumors due to the development of new imaging tools, such as diffusion …

Deep learning-based MRI diagnosis of internal joint derangement is an emerging field of
artificial intelligence, which offers many exciting possibilities for musculoskeletal radiology. A …

Purpose To evaluate the diagnostic performance of machine learning for discrimination
between low-grade and high-grade cartilaginous bone tumors based on radiomic …

To develop a machine learning (ML) model that predicts disease groups or autoantibodies
in patients with idiopathic inflammatory myopathies (IIMs) using muscle MRI radiomics …

This study aims to investigate the influence of interobserver manual segmentation variability
on the reproducibility of 2D and 3D unenhanced computed tomography (CT)-and magnetic …