AIMC Topic: Osteoarthritis, Knee
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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...
Managing class imbalance in the training of a large language model to predict patient selection for total knee arthroplasty: Results from the Artificial intelligence to Revolutionise the patient Care pathway in Hip and knEe aRthroplastY (ARCHERY) project.
The Knee
Feb 28, 2025
INTRODUCTION: This study set out to test the efficacy of different techniques used to manage to class imbalance, a type of data bias, in application of a large language model (LLM) to predict patient selection for total knee arthroplasty (TKA).
Identify the potential target of efferocytosis in knee osteoarthritis synovial tissue: a bioinformatics and machine learning-based study.
Frontiers in immunology
Feb 27, 2025
INTRODUCTION: Knee osteoarthritis (KOA) is a degenerative joint disease characterized by the progressive deterioration of cartilage and synovial inflammation. A critical mechanism in the pathogenesis of KOA is impaired efferocytosis in synovial tissu...
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...
Deep learning-based clustering for endotyping and post-arthroplasty response classification using knee osteoarthritis multiomic data.
Annals of the rheumatic diseases
Feb 12, 2025
OBJECTIVES: Primary knee osteoarthritis (KOA) is a heterogeneous disease with clinical and molecular contributors. Biofluids contain microRNAs and metabolites that can be measured by omic technologies. Multimodal deep learning is adept at uncovering ...
Biopsychosocial based machine learning models predict patient improvement after total knee arthroplasty.
Scientific reports
Feb 10, 2025
Total knee arthroplasty (TKA) is an effective treatment for end stage osteoarthritis. However, biopsychosocial features are not routinely considered in TKA clinical decision-making, despite increasing evidence to support their role in patient recover...
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...
Statin use and longitudinal bone marrow lesion burden: analysis of knees without osteoarthritis from the Osteoarthritis Initiative study.
Skeletal radiology
Jan 31, 2025
OBJECTIVES: Knee subchondral bone marrow lesions (BMLs) are one of the hallmark features of structural osteoarthritis (OA) and are potential targets for statins' disease-modifying effect. We aimed to determine the association between statin use and l...
A Deep Learning Tool for Minimum Joint Space Width Calculation on Antero-posterior Knee Radiographs.
The Journal of arthroplasty
Jan 27, 2025
BACKGROUND: Minimum joint space width (mJSW) is an important continuous quantitative metric of osteoarthritis progression in the knee. The purpose of this study was to develop an automated measurement algorithm for mJSW in the medial and lateral comp...
Prediction of the Serial Alignment Change after Opening-Wedge High Tibial Osteotomy Based on Coronal Plane Alignment of the Knee Using Machine Learning Algorithm.
The journal of knee surgery
Jan 27, 2025
Categorization of alignment into phenotypes can be useful for predicting and analyzing postoperative alignment changes after opening-wedge high tibial osteotomy (OWHTO). The purposes of this study were to (1) develop a machine learning model for the ...
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