Latest AI and machine learning research in rheumatology for healthcare professionals.
With the ever-increasing number of artificial intelligence (AI) systems, mitigating risks associated...
BACKGROUND: Artificial intelligence (AI) is reshaping healthcare, using machine and deep learning (D...
Deep learning models are being adopted and applied across various critical medical tasks, yet they a...
Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease during childhood and adoles...
OBJECTIVE: To establish a diagnostic model for scleroderma by combining machine learning and artific...
Tumor molecular data sets are becoming increasingly complex, making it nearly impossible for humans ...
BACKGROUND: Childhood Sjögren's disease is a rare, underdiagnosed, and poorly-understood condition. ...
Avian reoviruses continue to cause disease in turkeys with varied pathogenicity and tissue tropism. ...
INTRODUCTION: Instagram is a popular social networking platform for sharing photos with a large prop...
Metabolite-associated cell communications play critical roles in maintaining the normal biological f...
Aging entails gradual functional decline influenced by interconnected factors. Multiple hallmarks pr...
BACKGROUND: This paper looks at how AI and machine learning have been applied over the last ten year...
Currently, the main therapeutic methods for cancer include surgery, radiation therapy, and chemother...
The programmed cell death protein 1 (PD-1, CD279) is an important therapeutic target in many oncolog...
INTRODUCTION: Indonesian civilization extensively uses traditional medicine to cure illnesses and pr...
Dear Editor, Ticks carry many diseases, bacteria, and viruses and represent a very important healthc...
PURPOSE: To observe the anti-caries effect of transgenic tomato anti-caries vaccine after immunizati...
The correlation between IgE anti-BP180 NC16A autoantibody and disease activity of bullous pemphigoid...