AIMC Topic: Knee Joint
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Patellar tilt calculation utilizing artificial intelligence on CT knee imaging.
The Knee
Mar 13, 2025
BACKGROUND: In the diagnosis of patellar instability, three-dimensional (3D) imaging enables measurement of a wide range of metrics. However, measuring these metrics can be time-consuming and prone to error due to conducting 2D measurements on 3D obj...
A machine learning approach using gait parameters to cluster TKA subjects into stable and unstable joints for discovery analysis.
The Knee
Mar 11, 2025
BACKGROUND: Patient-reported joint instability after total knee arthroplasty (TKA) is difficult to quantify objectively. Here, we apply machine learning to cluster TKA subjects using nine literature-proposed gait parameters as knee instability predic...
AI classification of knee prostheses from plain radiographs and real-world applications.
European journal of orthopaedic surgery & traumatology : orthopedie traumatologie
Mar 11, 2025
PURPOSE: Total knee arthroplasty (TKA) is considered the gold standard treatment for end-stage knee osteoarthritis. Common complications associated with TKA include implant loosening and periprosthetic fractures, which often require revision surgery ...
Power-free knee rehabilitation robot for home-based isokinetic training.
Nature communications
Mar 8, 2025
Robot-assisted isokinetic training has been widely adopted for knee rehabilitation. However, existing rehabilitation facilities are often heavy, bulky, and extremely energy-consuming, which limits the rehabilitation opportunities only at designated h...
Comparison of predictive models for knee pain and analysis of individual and physical activity variables using interpretable machine learning.
The Knee
Mar 4, 2025
BACKGROUND: Knee pain is associated with not only individual factors such as age and obesity but also physical activity factors such as occupational activities and exercise, which has a significant impact on the lives of adults and the elderly.
An AI-based system for fully automated knee alignment assessment in standard AP knee radiographs.
The Knee
Mar 3, 2025
BACKGROUND: Accurate assessment of knee alignment in pre- and post-operative radiographs is crucial for knee arthroplasty planning and evaluation. Current methods rely on manual alignment assessment, which is time-consuming and error-prone. This stud...
A deep learning and statistical shape modeling-based method for assessing intercondylar notch volume in anterior cruciate ligament reconstruction.
The Knee
Feb 28, 2025
BACKGROUND: Anterior cruciate ligament (ACL) reconstruction is a widely performed procedure for ACL injury, but there are several factors which may lead to re-rupture or clinical failure. An intercondylar notch (or fossa) that is narrower may increas...
Comparative analysis of machine learning and deep learning algorithms for knee arthritis detection using YOLOv8 models.
Journal of X-ray science and technology
Feb 26, 2025
Knee arthritis is a prevalent joint condition that affects many people worldwide. Early detection and appropriate treatment are essential to slow the disease's progression and enhance patients' quality of life. In this study, various machine learning...
Development of a Wearable Sleeve-Based System Combining Polymer Optical Fiber Sensors and an LSTM Network for Estimating Knee Kinematics.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Feb 13, 2025
This study presents a novel wearable solution integrating Polymer Optical Fiber (POF) sensors into a knee sleeve to monitor knee flexion/extension (F/E) patterns during walking. POF sensors offer advantages such as flexibility, light weight, and robu...
Generating synthetic past and future states of Knee Osteoarthritis radiographs using Cycle-Consistent Generative Adversarial Neural Networks.
Computers in biology and medicine
Feb 9, 2025
Knee Osteoarthritis (KOA), a leading cause of disability worldwide, is challenging to detect early due to subtle radiographic indicators. Diverse, extensive datasets are needed but are challenging to compile because of privacy, data collection limita...
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