Rheumatology

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

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Application of serum SERS technology combined with deep learning algorithm in the rapid diagnosis of immune diseases and chronic kidney disease.

Surface-enhanced Raman spectroscopy (SERS), as a rapid, non-invasive and reliable spectroscopic dete...

Natural language processing of online support group postings reveals patients' perspectives on strategies for managing psoriasis.

Psoriasis is a chronic skin disorder, and patients encounter high physical and psychosocial burdens....

Application of artificial neural network in daily prediction of bleeding in ICU patients treated with anti-thrombotic therapy.

OBJECTIVES: Anti-thrombotic therapy is the basis of thrombosis prevention and treatment. Bleeding is...

Safety evaluation and effects of cascara pulp Gayo Arabica coffee cream as anti-photoaging in animal model.

Prolonged sunlight and ultraviolet (UV) exposure causes premature skin aging called photoaging and c...

[From conventional to cutting edge imaging in rheumatology].

Imaging instruments, such as conventional X‑ray, ultrasound and magnetic resonance imaging (MRI) are...

Urine and serum metabolic profiling combined with machine learning for autoimmune disease discrimination and classification.

Precision diagnosis and classification of autoimmune diseases (ADs) is challenging due to the obscur...

Cheminformatics and machine learning approaches for repurposing anti-viral compounds against monkeypox virus thymidylate kinase.

One of the emerging epidemic concerns is Monkeypox disease which is spreading globally. This disease...

Virtual screening strategy for anti-DPP-IV natural flavonoid derivatives based on machine learning.

Flavonoids, especially their inhibitory effect on DPP-IV activity, have been widely recognized for t...

Anti-photoaging effects of canola meal extract on human dermal fibroblasts against UVB-induced oxidative stress.

Canola meal, a by-product of canola oil processing, is a source of bioactive compounds that show ant...

A deep learning-based drug repurposing screening and validation for anti-SARS-CoV-2 compounds by targeting the cell entry mechanism.

The recent outbreak of Corona Virus Disease 2019 (COVID-19) caused by severe acute respiratory syndr...

Glucose-6-phosphate dehydrogenase deficiency with coinherited Gaucher disease: A rare association.

Anemia coexisting with Gaucher disease (GD) is often associated with non-hemolytic processes. Few ca...

Interaction of systemic drugs causing ocular toxicity with organic cation transporter: an artificial intelligence prediction.

Chronic disease patients (cancer, arthritis, cardiovascular diseases) undergo long-term systemic dru...

Deep learning to automatically evaluate HER2 gene amplification status from fluorescence in situ hybridization images.

Human epidermal growth factor receptor 2 (HER2) gene amplification helps identify breast cancer pati...

Anti-Synchronization of Discrete-Time Fuzzy Memristive Neural Networks via Impulse Sampled-Data Communication.

This work is concerned with the anti-synchronization (A-S) of drive-response (D-R) memristive neural...

Assessing facial weakness in myasthenia gravis with facial recognition software and deep learning.

OBJECTIVE: Myasthenia gravis (MG) is an autoimmune disease leading to fatigable muscle weakness. Ext...

Self-Adhesive, Anti-Freezing MXene-Based Hydrogel Strain Sensor for Motion Monitoring and Handwriting Recognition with Deep Learning.

Flexible strain sensors based on self-adhesive, high-tensile, super-sensitive conductive hydrogels h...

Machine learning-based drug design for identification of thymidylate kinase inhibitors as a potential anti-Mycobacterium tuberculosis.

The rise of antibiotic-resistant Mycobacterium tuberculosis (Mtb) has reduced the availability of me...

Biologically Interpretable Deep Learning To Predict Response to Immunotherapy In Advanced Melanoma Using Mutations and Copy Number Variations.

Only 30-40% of advanced melanoma patients respond effectively to immunotherapy in clinical practice,...

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