AIMC Topic: Knee Joint

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Lightweight early detection of knee osteoarthritis in athletes.

Scientific reports
Osteoarthritis (OA) is a prevalent condition among athletes, characterized by the progressive degradation of joint cartilage, particularly in weight-bearing joints such as the knees. Early detection is critical for effective management and prevention...

Predicting knee osteoarthritis progression using neural network with longitudinal MRI radiomics, and biochemical biomarkers: A modeling study.

PLoS medicine
BACKGROUND: Knee osteoarthritis (KOA) worsens both structurally and symptomatically, yet no model predicts KOA progression using Magnetic Resonance Image (MRI) radiomics and biomarkers. This study aimed to develop and test the longitudinal Load-Beari...

Distribution of interscan measurement error in AI-based 3D MRI analysis of knee cartilage thickness in osteoarthritis.

PloS one
PURPOSE: A novel AI-based 3D analysis system was developed to automatically extract bone and cartilage from MRI data and provide average cartilage thickness. This study aimed to analyze the interscan measurement error of knee cartilage thickness in o...

An AI-driven video based goniometer for knee joint range of motion (ROM) Assessment: Reliability and validity compared to traditional goniometry.

Computers in biology and medicine
BACKGROUND: Accurate measurement of knee joint range of motion (ROM) is crucial in clinical and rehabilitation settings. Traditional goniometry, which is widely used, requires calibration and is subject to human errors and measurement inconsistencies...

Knee osteoarthritis prediction from gait kinematics: Exploring the potential of deep neural networks and transfer learning methods for time series classification.

Journal of biomechanics
Recent advances in artificial intelligence methods have allowed improved disease diagnosis using fast and low-cost protocols. The present study explored the potential of different deep neural networks (DNNs) and transfer learning methods to detect kn...

[Update 2025: Biomechanics and kinematics after total knee arthroplasty (TKA)].

Orthopadie (Heidelberg, Germany)
BACKGROUND: In order to optimise clinical outcomes after primary total knee arthroplasty (TKA), research has refocused on the knee joint's biomechanical characteristics. Beyond implant design and alignment philosophy, the restoration of natural joint...

Applying binary mixed model to predict knee osteoarthritis pain.

PloS one
Data used to understand knee osteoarthritis (KOA) often involves knee-level, rather than person-level information. Failure to account for the correlation between joints within a person may lead to inaccurate inferences. The aim of this study was to d...

Deep learning based classification of tibio-femoral knee osteoarthritis from lateral view knee joint X-ray images.

Scientific reports
Design an effective deep learning-driven method to locate and classify the tibio-femoral knee joint space width (JSW) with respect to both anterior-posterior (AP) and lateral views. Compare the results and see how successfully a deep learning approac...

Your turn: At home turning angle estimation for Parkinson's disease severity assessment.

Artificial intelligence in medicine
People with Parkinson's Disease (PD) often experience progressively worsening gait, including changes in how they turn around, as the disease progresses. Existing clinical rating tools are not capable of capturing hour-by-hour variations of PD sympto...

Same-model and cross-model variability in knee cartilage thickness measurements using 3D MRI systems.

PloS one
PURPOSE: Magnetic Resonance Imaging (MRI) based three-dimensional analysis of knee cartilage has evolved to become fully automatic. However, when implementing these measurements across multiple clinical centers, scanner variability becomes a critical...