Arthritis

Modelling disease risk for amyloid A (AA) amyloidosis in non-human primates using machine learning.

Amyloid A (AA) amyloidosis is found in humans and non-human primates, but quantifying disease risk prior to clinical symptoms is challenging. We applied machine learning to identify the best predictors of amyloidosis in rhesus macaques from available clinical and pathology records. To explore potential biomarkers, we also assessed whether changes in circulating serum amyloid A (SAA) or lipoprotei...

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 adults. Early detection and intervention can help slow down the OA degeneration. Physicians' grading based on visual inspection is subjective, varied across interpreters, and highly relied on their experience. In this paper, we successively apply two deep convolutional neural networks (CNN) to autom...

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 population is mostly affected by rheumatic diseases. With t...

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

OBJECTIVES: This study aims to compare the serum pyridinoline (Pyd) levels between rheumatoid arthritis (RA) patients and healthy controls and to dete...

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 potentially distinct phenotypes. The purpose of this study...

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 osteoarthritis. A correct prediction of osteoarthri...

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 difficulty in extracting accurate disease phenotype da...

Neural networks for automatic scoring of arthritis disease activity on ultrasound images.

BACKGROUND: The development of standardised methods for ultrasound (US) scanning and evaluation of synovitis activity by the OMERACT-EULAR Synovitis S...

Diagnosing osteoarthritis from T maps using deep learning: an analysis of the entire Osteoarthritis Initiative baseline cohort.

OBJECTIVE: We aim to study to what extent conventional and deep-learning-based T relaxometry patterns are able to distinguish between knees with and w...

Machine learning identifies an immunological pattern associated with multiple juvenile idiopathic arthritis subtypes.

OBJECTIVES: Juvenile idiopathic arthritis (JIA) is the most common class of childhood rheumatic diseases, with distinct disease subsets that may have ...

Detection of rheumatoid arthritis from hand radiographs using a convolutional neural network.

INTRODUCTION: Plain hand radiographs are the first-line and most commonly used imaging methods for diagnosis or differential diagnosis of rheumatoid a...

Analysis of differentially expressed genes in rheumatoid arthritis and osteoarthritis by integrated microarray analysis.

BACKGROUND: Rheumatoid arthritis (RA) and osteoarthritis (OA) were two major types of joint diseases. This study aimed to explore the mechanism underl...

Assessment of a Deep Learning Model Based on Electronic Health Record Data to Forecast Clinical Outcomes in Patients With Rheumatoid Arthritis.

IMPORTANCE: Knowing the future condition of a patient would enable a physician to customize current therapeutic options to prevent disease worsening, ...

Bone texture analysis for prediction of incident radiographic hip osteoarthritis using machine learning: data from the Cohort Hip and Cohort Knee (CHECK) study.

OBJECTIVE: To assess the ability of radiography-based bone texture variables in proximal femur and acetabulum to predict incident radiographic hip ost...

The Effect of the Prethanol Extract of Trifolium pratense Leaves on Interleukin-1β-Induced Cartilage Matrix Degradation in Primary Rat Chondrocytes.

BACKGROUND: Osteoarthritis (OA) is a degenerative joint disease, characterized by cartilage degradation and inflammation. The proinflammatory cytokine...

A decision support tool for early detection of knee OsteoArthritis using X-ray imaging and machine learning: Data from the OsteoArthritis Initiative.

This paper presents a fully developed computer aided diagnosis (CAD) system for early knee OsteoArthritis (OA) detection using knee X-ray imaging and ...

Rheumatoid Arthritis: Atherosclerosis Imaging and Cardiovascular Risk Assessment Using Machine and Deep Learning-Based Tissue Characterization.

PURPOSE OF THE REVIEW: Rheumatoid arthritis (RA) is a chronic, autoimmune disease which may result in a higher risk of cardiovascular (CV) events and ...

Total Knee Arthroplasty Is Safe and Successful in Patients With Klippel-Trénaunay Syndrome.

BACKGROUND: Klippel-Trénaunay syndrome (KTS) is a severe vascular malformation that can lead to hypertrophic osteoarthritis. Total knee arthroplasty (...

Serum hepcidin level and rheumatoid arthritis disease activity.

OBJECTIVE: The present study aimed to determine the relationship between the serum hepcidin level and disease activity in patients with rheumatoid art...

Serum Procalcitonin and Presepsin Levels in Patients with Generalized Pustular Psoriasis.

Patients with generalized pustular psoriasis (GPP) often present with symptoms that must be differentiated from sepsis. Procalcitonin (PCT) and presep...