Latest AI and machine learning research in orthopedics for healthcare professionals.
OBJECTIVES: This study aimed to clarify the performance of MRI-based deep learning classification models in diagnosing temporomandibular joint osteoarthritis (TMJ-OA) and to compare the developed diagnostic assistance with human observers.
Purpose To develop a deep learning tool for the automatic segmentation of the spinal cord and intramedullary lesions in spinal cord injury (SCI) on T2-weighted MRI scans. Materials and Methods This retrospective study included MRI data acquired between July 2002 and February 2023. The data consisted of T2-weighted MRI scans acquired using different scanner manufacturers with various image resoluti...
OBJECTIVES: To summarize the current evidence on the performance of artificial intelligence (AI) algorithms for the temporomandibular joint (TMJ) disc...
OBJECTIVES: The purpose of this study was to propose a machine learning model and assess its ability to classify temporomandibular joint (TMJ) disc di...
BACKGROUND: Osteoporosis (OP) is one of the most common diseases in the elderly population. It is mostly treated with medication, but drug research an...
Robotic joint surgery (RJS) has demonstrated high precision and reproducibility in total hip and knee arthroplasty,the integration of artificial intel...
BACKGROUND: Palliative spine radiation therapy is prone to treatment at the wrong anatomic level. We developed a fully automated deep learning-based s...
INTRODUCTION: In Iran, the assessment of osteoporosis through tools like dual-energy X-ray absorptiometry poses significant challenges due to their hi...
AIM: This study aimed to develop a reliable and efficient system for predicting and locating rib fractures in medical images using an ensemble of conv...
BACKGROUND: Osteoporotic fractures (OPF) pose a public health issue, imposing significant burdens on families and societies worldwide. Currently, ther...
Background Deep learning (DL) methods can improve accelerated MRI but require validation against an independent reference standard to ensure robustnes...
BACKGROUND: Large language models (LLMs) have many clinical applications. However, the comparative performance of different LLMs on orthopedic board s...
BACKGROUND: Spinal image denoising plays a vital role in the accurate diagnosis of disc herniation (DH).
BACKGROUND: Artificial intelligence (AI) is a promising and powerful technology with increasing use in orthopedics. The global morbidity of knee arthr...
Computer-aided diagnosis (CAD) systems have greatly improved the interpretation of medical images by radiologists and surgeons. However, current CAD...
Calibration to experimental data is vital when developing subject-specific models towards developing digital twins. Yet, to date, subject-specific m...
Audio-visual video parsing (AVVP) aims to recognize audio and visual event labels with precise temporal boundaries, which is quite challenging since...
Lumbar disk segmentation is essential for diagnosing and curing spinal disorders by enabling precise detection of disk boundaries in medical imaging...
Vertebral compression fractures (VCFs) are a common and potentially serious consequence of osteoporosis. Yet, they often remain undiagnosed. Opportu...
Deep neural network (DNN)-based joint source and channel coding is proposed for privacy-aware end-to-end image transmission against multiple eavesdr...