Publications by authors named "Gregoire Attane"
Rationale And Objectives: Interpreting radiographs in emergency settings is stressful and a burden for radiologists. The main objective was to assess the performance of three commercially available artificial intelligence (AI) algorithms for detecting acute peripheral fractures on radiographs in daily emergency practice.
Materials And Methods: Radiographs were collected from consecutive patients admitted for skeletal trauma at our emergency department over a period of 2 months.
The interest of researchers, clinicians and radiologists, in artificial intelligence (AI) continues to grow. Deep learning is a subset of machine learning, in which the computer algorithm itself can determine the optimal imaging features to answer a clinical question. Convolutional neural networks are the most common architecture for performing deep learning on medical images.
View Article and Find Full Text PDFObjective: The lack of specificity of the ASAS MRI criteria for non-radiographic axial spondylarthritis (NR-axSpA) justifies the evaluation of the discriminatory capacity of other MRI abnormalities in the sacroiliac joints and dorsolumbar spine.
Methods: In patients hospitalized for inflammatory lumbar back pain, the diagnostic performance (sensitivity, specificity, positive likelihood ratio (PLR)) of MRI abnormalities was calculated using the rheumatologist expert opinion as a reference: (i) sacroiliac joints: Bone marrow edema (BME) (number and location), extended edema>1cm (deep lesion), fatty metaplasia (number), erosion (number and location), backfill. (ii) Dorsolumbar spine: BME (number and location), fatty metaplasia (number), posterior segment involvement.