Journal of imaging informatics in medicine
Sep 12, 2024
PURPOSE: To develop a deep learning model for automated classification of orthopedic hardware on pelvic and hip radiographs, which can be clinically implemented to decrease radiologist workload and improve consistency among radiology reports.
BACKGROUND: Hip arthroscopy has seen a significant surge in utilization, but complications remain, and optimal functional outcomes are not guaranteed. Artificial intelligence (AI) has emerged as an effective supportive decision-making tool for surgeo...
Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Jul 21, 2024
PURPOSE: The aim of this study was to conduct a systematic review and meta-analysis on the reliability and applicability of artificial intelligence (AI)-based analysis of leg axis parameters. We hypothesized that AI-based leg axis measurements would ...
Topics in magnetic resonance imaging : TMRI
Jul 12, 2024
OBJECTIVES: The radiological imaging industry is developing and starting to offer a range of novel artificial intelligence software solutions for clinical radiology. Deep learning reconstruction of magnetic resonance imaging data seems to allow for t...
AI-powered segmentation of hip and knee bony anatomy has revolutionized orthopedics, transforming pre-operative planning and post-operative assessment. Despite the remarkable advancements in AI algorithms for medical imaging, the potential for biases...
Wearable robots are emerging as a viable and effective solution for assisting and enabling people who suffer from balance and mobility disorders. Virtual prototyping is a powerful tool to design robots, preventing the costly iterative physical protot...
The use of wearable sensors, such as inertial measurement units (IMUs), and machine learning for human intent recognition in health-related areas has grown considerably. However, there is limited research exploring how IMU quantity and placement affe...
BACKGROUND: Dissatisfaction after total knee arthroplasty (TKA) ranges from 15 to 30%. While patient selection may be partially responsible, morphological and reconstructive challenges may be determinants. Preoperative computed tomography (CT) scans ...
OBJECTIVE: To develop and validate a neural network to estimate hip contact forces (HCF), and lower body kinematics and kinetics during walking in individuals with hip osteoarthritis (OA) using synthesised anatomical key points and electromyography. ...
Computer methods in biomechanics and biomedical engineering
Feb 8, 2024
The application of machine learning in the field of motion capture research is growing rapidly. The purpose of the study is to implement a long-short term memory (LSTM) model able to predict sagittal plane hip joint moment (HJM) across three distinct...
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