Rheumatology

Arthritis

Latest AI and machine learning research in arthritis for healthcare professionals.

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Development of a Machine Learning Model to Predict the Use of Surgery in Patients With Rheumatoid Arthritis.

OBJECTIVE: One in five patients with rheumatoid arthritis (RA) rely on surgery to restore joint func...

Predicting the onset of end-stage knee osteoarthritis over two- and five-years using machine learning.

OBJECTIVE: Identifying participants who will progress to advanced stage in knee osteoarthritis (KOA)...

Multicentric development and validation of a multi-scale and multi-task deep learning model for comprehensive lower extremity alignment analysis.

Osteoarthritis of the knee, a widespread cause of knee disability, is commonly treated in orthopedic...

Automatic hip osteoarthritis grading with uncertainty estimation from computed tomography using digitally-reconstructed radiographs.

PURPOSE: Progression of hip osteoarthritis (hip OA) leads to pain and disability, likely leading to ...

Trustworthy deep learning framework for the detection of abnormalities in X-ray shoulder images.

Musculoskeletal conditions affect an estimated 1.7 billion people worldwide, causing intense pain an...

Hip contact forces can be predicted with a neural network using only synthesised key points and electromyography in people with hip osteoarthritis.

OBJECTIVE: To develop and validate a neural network to estimate hip contact forces (HCF), and lower ...

All that Glitters Is not Gold: Type-I Error Controlled Variable Selection from Clinical Trial Data.

Clinical trials are primarily conducted to estimate causal effects, but the data collected can also ...

Using ChatGPT-Like Solutions to Bridge the Communication Gap Between Patients With Rheumatoid Arthritis and Health Care Professionals.

The communication gap between patients and health care professionals has led to increased disputes a...

Analysis of robot-specific operative time and surgical team anxiety level and its effect on alignment during robot-assisted TKA.

Adapting to robotic-assisted (RA) total knee arthroplasty (TKA) is hindered by the surgeon's fear of...

Classification of inertial sensor-based gait patterns of orthopaedic conditions using machine learning: A pilot study.

Elderly patients often have more than one disease that affects walking behavior. An objective tool t...

Machine Learning Models for Low Back Pain Detection and Factor Identification: Insights From a 6-Year Nationwide Survey.

This study aimed to enhance performance, identify additional predictors, and improve the interpretab...

Application of deep learning for automated diagnosis and classification of hip dysplasia on plain radiographs.

BACKGROUND: Hip dysplasia is a condition where the acetabulum is too shallow to support the femoral ...

Deep learning based detection of osteophytes in radiographs and magnetic resonance imagings of the knee using 2D and 3D morphology.

In this study, we investigated the discriminative capacity of knee morphology in automatic detection...

A perspective on the evolution of semi-quantitative MRI assessment of osteoarthritis: Past, present and future.

OBJECTIVE: This perspective describes the evolution of semi-quantitative (SQ) magnetic resonance ima...

Pain-free oral delivery of biologic drugs using intestinal peristalsis-actuated microneedle robots.

Biologic drugs hold immense promise for medical treatments, but their oral delivery remains a daunti...

Frankincense preparation promotes formation of inflammation-resolving lipid mediators by manipulating lipoxygenases in human innate immune cells.

Frankincense preparations are frequently used as traditional anti-inflammatory remedies in folk med...

Synthetic Knee MRI T Maps as an Avenue for Clinical Translation of Quantitative Osteoarthritis Biomarkers.

A 2D U-Net was trained to generate synthetic T maps from T maps for knee MRI to explore the feasibil...

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