Rheumatology

Arthritis

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

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Deep segmentation leverages geometric pose estimation in computer-aided total knee arthroplasty.

Knee arthritis is a common joint disease that usually requires a total knee arthroplasty. There are ...

Deep Learning for Lesion Detection, Progression, and Prediction of Musculoskeletal Disease.

Deep learning is one of the most exciting new areas in medical imaging. This review article provides...

Machine Learning to Predict Anti-Tumor Necrosis Factor Drug Responses of Rheumatoid Arthritis Patients by Integrating Clinical and Genetic Markers.

OBJECTIVE: Accurate prediction of treatment responses in rheumatoid arthritis (RA) patients can prov...

Antibiotic therapy in patients with high prostate-specific antigen: Is it worth considering? A systematic review.

: To address the question of whether antibiotic therapy can obviate the need for prostate biopsy (PB...

Antioxidant, Anti-Melanogenic and Anti-Wrinkle Effects of .

In this study, the antioxidant, anti-xanthine oxidase, anti-melanogenic and anti-wrinkle effects of ...

Super-resolution reconstruction of knee magnetic resonance imaging based on deep learning.

BACKGROUND AND OBJECTIVE: With the rapid development of medical imaging and intelligent diagnosis, a...

Age and Sex Estimation Using Artificial Intelligence From Standard 12-Lead ECGs.

BACKGROUND: Sex and age have long been known to affect the ECG. Several biologic variables and anato...

Estimation of Vertical Ground Reaction Force Using Low-Cost Insole With Force Plate-Free Learning From Single Leg Stance and Walking.

For the evaluation of pathological gait, a machine learning-based estimation of the vertical ground ...

Identifying key gait features associated with the radiological grade of knee osteoarthritis.

PURPOSE: Knee osteoarthritis (KOA) is characterized by pain and decreased gait function. This study ...

Minimally Invasive Approach for Diagnosing TMJ Osteoarthritis.

This study's objectives were to test correlations among groups of biomarkers that are associated wit...

Utility of deep learning super-resolution in the context of osteoarthritis MRI biomarkers.

BACKGROUND: Super-resolution is an emerging method for enhancing MRI resolution; however, its impact...

Fully automatic knee osteoarthritis severity grading using deep neural networks with a novel ordinal loss.

Knee osteoarthritis (OA) is one major cause of activity limitation and physical disability in older ...

Automatic localization of anatomical regions in medical ultrasound images of rheumatoid arthritis using deep learning.

The pace of population aging is growing faster worldwide. The quality of life of the aging populatio...

Serum Pyridinoline is Associated With Radiographic Joint Erosions in Rheumatoid Arthritis.

OBJECTIVES: This study aims to compare the serum pyridinoline (Pyd) levels between rheumatoid arthri...

A machine learning approach to knee osteoarthritis phenotyping: data from the FNIH Biomarkers Consortium.

OBJECTIVE: Knee osteoarthritis (KOA) is a heterogeneous condition representing a variety of potentia...

A Deep Neural Network-Based Method for Early Detection of Osteoarthritis Using Statistical Data.

A large number of people suffer from certain types of osteoarthritis, such as knee, hip, and spine o...

Automated feature selection of predictors in electronic medical records data.

The use of Electronic Health Records (EHR) for translational research can be challenging due to diff...

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