Machine learning for clustering and classification of early knee osteoarthritis using single-leg standing kinematics
Objective Detection of early osteoarthritis (EOA) of the knee is crucial for effective management and improved outcomes. This study investigated the application of machine learning techniques to single-leg standing (SLS) kinematics to classify and predict EOA. (1) To identify distinct groups based o...
Saved in:
| Main Authors: | Ui-Jae Hwang, Kyu Sung Chung, Sung-Min Ha |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2025-03-01
|
| Series: | Digital Health |
| Online Access: | https://doi.org/10.1177/20552076251326226 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Clustering and classification of early knee osteoarthritis using machine-learning analysis of step-up and down test kinematics in recreational table tennis players
by: Ui-jae Hwang, et al.
Published: (2025-05-01) -
The Difference in Supine versus Standing Plain Radiograph of the Knee in Patients with Knee Osteoarthritis
by: Musa AA, et al.
Published: (2025-07-01) -
The Effect of Correction Algorithms on Knee Kinematics and Kinetics during Gait of Patients with Knee Osteoarthritis
by: Hanna Ulbricht, et al.
Published: (2020-01-01) -
Between-Day Reliability of Kinematic Variables Using Markerless Motion Capture for Single-Leg Squat and Single-Leg Landing Tasks
by: Matias Yoma, et al.
Published: (2025-08-01) -
The epidemic of alignment classifications in total knee arthroplasty forgives the kinematic of the human knee
by: Pier Francesco Indelli
Published: (2024-10-01)