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Osteoarthritis, Knee

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Association of Machine Learning-Based Predictions of Medial Knee Contact Force With Cartilage Loss Over 2.5 Years in Knee Osteoarthritis.

Arthritis & rheumatology (Hoboken, N.J.)
OBJECTIVE: The relationship between in vivo knee load predictions and longitudinal cartilage changes has not been investigated. We undertook this study to develop an equation to predict the medial tibiofemoral contact force (MCF) peak during walking ...

Equal bony resection of distal and posterior femur will lead to flexion/extension gap inequality in robot-assisted cruciate-retaining TKA.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: Joint imbalance has become one of the main reasons for early revision after total knee arthroplasty (TKA) and it is directly related to the surgical technique. Therefore, a better understanding of how much bone has to be removed to obtain a ...

Automated detection of patellofemoral osteoarthritis from knee lateral view radiographs using deep learning: data from the Multicenter Osteoarthritis Study (MOST).

Osteoarthritis and cartilage
OBJECTIVE: To assess the ability of imaging-based deep learning to detect radiographic patellofemoral osteoarthritis (PFOA) from knee lateral view radiographs.

Deep learning approach to predict pain progression in knee osteoarthritis.

Skeletal radiology
OBJECTIVE: To develop and evaluate deep learning (DL) risk assessment models for predicting pain progression in subjects with or at risk of knee osteoarthritis (OA).

Deep learning-based algorithm for assessment of knee osteoarthritis severity in radiographs matches performance of radiologists.

Computers in biology and medicine
UNLABELLED: A fully-automated deep learning algorithm matched performance of radiologists in assessment of knee osteoarthritis severity in radiographs using the Kellgren-Lawrence grading system.

Machine learning classification on texture analyzed T2 maps of osteoarthritic cartilage: oulu knee osteoarthritis study.

Osteoarthritis and cartilage
OBJECTIVE: To introduce local binary pattern (LBP) texture analysis to cartilage osteoarthritis (OA) research and compare the performance of different classification systems in discrimination of OA subjects from healthy controls using gray-level co-o...

Machine learning-augmented and microspectroscopy-informed multiparametric MRI for the non-invasive prediction of articular cartilage composition.

Osteoarthritis and cartilage
BACKGROUND: Articular cartilage degeneration is the hallmark change of osteoarthritis, a severely disabling disease with high prevalence and considerable socioeconomic and individual burden. Early, potentially reversible cartilage degeneration is cha...

Deep learning for early detection of pathological changes in X-ray bone microstructures: case of osteoarthritis.

Scientific reports
Texture features are designed to quantitatively evaluate patterns of spatial distribution of image pixels for purposes of image analysis and interpretation. Unexplained variations in the texture patterns often lead to misinterpretation and undesirabl...