AIMC Topic: Osteoarthritis, Knee

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Multi-classifier prediction of knee osteoarthritis progression from incomplete imbalanced longitudinal data.

Scientific reports
Conventional inclusion criteria used in osteoarthritis clinical trials are not very effective in selecting patients who would benefit from a therapy being tested. Typically majority of selected patients show no or limited disease progression during a...

Automating three-dimensional osteoarthritis histopathological grading of human osteochondral tissue using machine learning on contrast-enhanced micro-computed tomography.

Osteoarthritis and cartilage
OBJECTIVE: To develop and validate a machine learning (ML) approach for automatic three-dimensional (3D) histopathological grading of osteochondral samples imaged with contrast-enhanced micro-computed tomography (CEμCT).

Development of automatic measurement for patellar height based on deep learning and knee radiographs.

European radiology
OBJECTIVES: To develop and evaluate the performance of a deep learning-based system for automatic patellar height measurements using knee radiographs.

Deep Learning Predicts Total Knee Replacement from Magnetic Resonance Images.

Scientific reports
Knee Osteoarthritis (OA) is a common musculoskeletal disorder in the United States. When diagnosed at early stages, lifestyle interventions such as exercise and weight loss can slow OA progression, but at later stages, only an invasive option is avai...

Assessment of knee pain from MR imaging using a convolutional Siamese network.

European radiology
OBJECTIVES: It remains difficult to characterize the source of pain in knee joints either using radiographs or magnetic resonance imaging (MRI). We sought to determine if advanced machine learning methods such as deep neural networks could distinguis...

Deep learning risk assessment models for predicting progression of radiographic medial joint space loss over a 48-MONTH follow-up period.

Osteoarthritis and cartilage
OBJECTIVE: To develop and evaluate deep learning (DL) risk assessment models for predicting the progression of radiographic medial joint space loss using baseline knee X-rays.

The Use of Artificial Intelligence in the Evaluation of Knee Pathology.

Seminars in musculoskeletal radiology
Artificial intelligence (AI) holds the potential to revolutionize the field of radiology by increasing the efficiency and accuracy of both interpretive and noninterpretive tasks. We have only just begun to explore AI applications in the diagnostic ev...

Toward automatic quantification of knee osteoarthritis severity using improved Faster R-CNN.

International journal of computer assisted radiology and surgery
PURPOSE: Knee osteoarthritis (OA) is a common disease that impairs knee function and causes pain. Radiologists usually review knee X-ray images and grade the severity of the impairments according to the Kellgren-Lawrence grading scheme. However, this...

Multimodal Machine Learning-based Knee Osteoarthritis Progression Prediction from Plain Radiographs and Clinical Data.

Scientific reports
Knee osteoarthritis (OA) is the most common musculoskeletal disease without a cure, and current treatment options are limited to symptomatic relief. Prediction of OA progression is a very challenging and timely issue, and it could, if resolved, accel...