Latest AI and machine learning research in rheumatology for healthcare professionals.
The evaluation of the leishmanicidal and trypanocidal activity of the hydroalcoholic extract of the bark of Mart. (EHCSR) was carried out to find an alternative treatment for parasitic diseases. EHCSR was prepared and used at four different concentrations (1000, 500, 250, 125 μg/mL) in assays for activity against Leishmania promastigotes using the species and and for trypanocidal activity usin...
UNLABELLED: Recent studies have posited that machine learning (ML) techniques accurately classify individuals with and without pain solely based on neuroimaging data. These studies claim that self-report is unreliable, making "objective" neuroimaging classification methods imperative. However, the relative performance of ML on neuroimaging and self-report data have not been compared. This study us...
Systemic erythematosus lupus (SLE) is a multisystemic autoimmune disease which has nephritis as one of the most striking manifestations. Although it c...
Putatively functional polymorphisms of one-carbon and xenobiotic metabolic pathways influence susceptibility for wide spectrum of diseases. The curren...
Candida albicans has become resistant to the commercially available, toxic, and expensive anti-Candida agents that are on the market. These factors fo...
This research examines the precision of an adaptive neuro-fuzzy computing technique in estimating the anti-obesity property of a potent medicinal plan...
We present the nanosurgery on the cytoskeleton of live cells using AFM based nanorobotics to achieve adhesiolysis and mimic the effect of pathophysiol...
Infrared small target detection (ISTD) remains challenging because tiny, low-contrast targets are easily overwhelmed by clutter, noise, or occlusion. ...
Background Unsupervised machine learning has become a cornerstone of computational phenotyping across clinical medicine, genomics, imaging, and multi-...
The Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K) is a crucial but labor-intensive tool for managing SLE. We developed a privac...
Background Pretreatment prediction of primary resistance to anti-PD-(L)1 therapy in advanced non-small-cell lung cancer (NSCLC) remains an unmet clini...
Objective: Chronic care requires sequential treatment under competing biomarker, safety, and cost constraints, yet clinical goal structures differ acr...
The rise of customized diffusion models has fueled a boom in personalized visual content creation, but it also introduces serious risks of malicious m...
Recent advances in Image-to-Video generation allow a single image to be animated into a convincing video under text guidance, raising serious copyrigh...
Aging is caused, fully in large part, by the progressive accumulation of damage, yet quantifying age-related damage across tissues and conditions rema...
Despite their remarkable performance, Vision Language Models (VLMs) incur substantial computational overhead due to the large number of visual tokens....
Five years after the discovery of persistent anti-Muslim bias in large language models, most evaluations remain confined to single-turn prompt complet...
Model fingerprinting, embedding user-specific identifiers (fingerprints) into generated outputs, has recently emerged as a popular solution to protect...
Despite advances in information extraction driven by deep learning and large language models, performance gaps remain in highly specialized biomedical...
Text-conditioned 3D generation has progressed rapidly for images and isolated objects, but producing a hand-object mesh remains challenging: the outpu...