BACKGROUND: Marker-less systems based on digital video cameras and deep learning for gait analysis could have a deep impact in clinical routine. A recently developed system has shown promising results in terms of joint center position but has not bee...
PURPOSE: We developed a tool for locating and grading knee osteoarthritis (OA) from digital X-ray images and illustrate the possibility of deep learning techniques to predict knee OA as per the Kellgren-Lawrence (KL) grading system. The purpose of th...
An important quality criterion for radiographs is the correct anatomical side marking. A deep neural network is evaluated to predict the correct anatomical side in radiographs of the knee acquired in anterior-posterior direction. In this retrospectiv...
BACKGROUND: Artificial Intelligence (AI)/Machine Learning (ML) applications have been proven efficient to improve diagnosis, to stratify risk, and to predict outcomes in many respective medical specialties, including in orthopaedics.
BACKGROUND: The cost-effectiveness of robotic-assisted unicompartmental knee arthroplasty (RA-UKA) remains unclear. Time-driven activity-based costing (TDABC) has been shown to accurately reflect true resource utilization. This study aimed to compare...
PURPOSE: Previous studies evaluating hindfoot and knee alignment have suggested compensation between the knee and the hindfoot deformities. However, these studies did not investigate the influence of the orientation of the subtalar axis on the result...
Because of the intense competition, table tennis requires players to bear a strong physiological load, which increases the risk of sports injury. Anterior cruciate ligament (ACL) is an important structure of the knee joint to maintain forward stabili...
Abnormal spasticity and associated synergistic patterns are the most common neuromuscular impairments affecting ankle-knee-hip interlimb coordinated gait kinematics and kinetics in patients with hemiparetic stroke. Although patients with hemiparetic ...
Nowadays, the use of wearable inertial-based systems together with machine learning methods opens new pathways to assess athletes' performance. In this paper, we developed a neural network-based approach for the estimation of the Ground Reaction Forc...
OBJECTIVE: To develop a machine learning-based prediction model for incident radiographic osteoarthritis (OA) of the knee over 8 years using MRI-based cartilage biochemical composition and knee joint structure, demographics, and clinical predictors i...