AIMC Topic: Osteoarthritis, Knee

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Feature Selection in Healthcare Datasets: Towards a Generalizable Solution.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: The increasing dimensionality of healthcare datasets presents major challenges for clinical data analysis and interpretation. This study introduces a scalable ensemble feature selection (FS) strategy optimized for multi-biom...

Role of Motion Tracking in Tele-Assessment of Functional Impairments in Individuals With Knee Osteoarthritis: A Scoping Review Protocol.

Musculoskeletal care
INTRODUCTION: Knee osteoarthritis (KOA) is a prevalent cause of disability, marked by functional impairments that significantly reduce quality of life. Emerging digital health tools-particularly artificial intelligence (AI) and motion tracking techno...

An AI system for continuous knee osteoarthritis severity grading: An anomaly detection inspired approach with few labels.

Artificial intelligence in medicine
The diagnostic accuracy and subjectivity of existing Knee Osteoarthritis (OA) ordinal grading systems has been a subject of on-going debate and concern. Existing automated solutions are trained to emulate these imperfect systems, whilst also being re...

Age and sex-specific differences of the intrafemoral and intratibial morphology using the Citak classification in patients undergoing total knee arthroplasty.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: Unlike established knee phenotype classifications, the recently introduced Citak classifications describe the intrafemoral and intratibial knee morphology. The aim of this study was to evaluate the distribution of Citak types A, B and C of t...

Predicting Knee Osteoarthritis Severity from Radiographic Predictors: Data from the Osteoarthritis Initiative.

Annals of biomedical engineering
PURPOSE: In knee osteoarthritis (KOA) treatment, preventive measures to reduce its onset risk are a key factor. Among individuals with radiographically healthy knees, however, future knee joint integrity and condition cannot be predicted by clinicall...

Estimation of time-to-total knee replacement surgery with multimodal modeling and artificial intelligence.

Computers in biology and medicine
BACKGROUND: The methods for predicting time-to-total knee replacement (TKR) do not provide enough information to make robust and accurate predictions.

Unveiling Prognostic and Diagnostic Biomarkers in Knee and Hip Osteoarthritis: A Targeted Review.

Discovery medicine
Osteoarthritis is a multifactorial condition marked by the gradual deterioration of joint cartilage, synovial inflammation, alterations in the subchondral bone and changes in the surrounding soft tissues. Clinical assessments and patient-reported out...

Using deep-learning based segmentation to enable spatial evaluation of knee osteoarthritis (SEKO) in rodent models.

Osteoarthritis and cartilage
OBJECTIVE: In preclinical models of osteoarthritis (OA), histology is commonly used to evaluate joint remodeling. The current study introduces a deep learning driven histological analysis pipeline for the spatial evaluation of knee osteoarthritis (SE...

Next-Level Prediction of Structural Progression in Knee Osteoarthritis: A Perspective.

International journal of molecular sciences
Osteoarthritis (OA) is a prevalent and disabling chronic disease, with knee OA being the most common form, affecting approximately 73% of individuals over 55 years. Traditional clinical assessments often fail to predict knee structural progression ac...