AIMC Topic: Autoimmune Diseases

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Deep learning-based prediction of autoimmune diseases.

Scientific reports
Autoimmune Diseases are a complex group of diseases caused by the immune system mistakenly attacking body tissues. Their etiology involves multiple factors such as genetics, environmental factors, and abnormalities in immune cells, making prediction ...

Advancing Optical Coherence Tomography Diagnostic Capabilities: Machine Learning Approaches to Detect Autoimmune Inflammatory Diseases.

Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society
BACKGROUND: In many parts of the world including India, the prevalence of autoimmune inflammatory diseases such as neuromyelitis optica spectrum disorders (NMOSD), myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), and multiple ...

InterDIA: Interpretable prediction of drug-induced autoimmunity through ensemble machine learning approaches.

Toxicology
Drug-induced autoimmunity (DIA) is a non-IgE immune-related adverse drug reaction that poses substantial challenges in predictive toxicology due to its idiosyncratic nature, complex pathogenesis, and diverse clinical manifestations. To address these ...

Artificial intelligence-based cardiovascular/stroke risk stratification in women affected by autoimmune disorders: a narrative survey.

Rheumatology international
Women are disproportionately affected by chronic autoimmune diseases (AD) like systemic lupus erythematosus (SLE), scleroderma, rheumatoid arthritis (RA), and Sjögren's syndrome. Traditional evaluations often underestimate the associated cardiovascul...

Quantitative fibrosis identifies biliary tract involvement and is associated with outcomes in pediatric autoimmune liver disease.

Hepatology communications
BACKGROUND: Children with autoimmune liver disease (AILD) may develop fibrosis-related complications necessitating a liver transplant. We hypothesize that tissue-based analysis of liver fibrosis by second harmonic generation (SHG) microscopy with art...

Artificial intelligence meets the world experts; updates and novel therapies in autoimmunity - The 14th international congress on autoimmunity 2024 (AUTO14), Ljubljana.

Autoimmunity reviews
The bi-annual international congress on autoimmunity is a huge opportunity for the medical community to discuss the latest updates in the field. During the 14th congress 2024 (AUTO14) in Ljubljana, artificial intelligence (AI) occupied special attent...

A Multi-task learning U-Net model for end-to-end HEp-2 cell image analysis.

Artificial intelligence in medicine
Antinuclear Antibody (ANA) testing is pivotal to help diagnose patients with a suspected autoimmune disease. The Indirect Immunofluorescence (IIF) microscopy performed with human epithelial type 2 (HEp-2) cells as the substrate is the reference metho...

Machine learning for precision diagnostics of autoimmunity.

Scientific reports
Early and accurate diagnosis is crucial to prevent disease development and define therapeutic strategies. Due to predominantly unspecific symptoms, diagnosis of autoimmune diseases (AID) is notoriously challenging. Clinical decision support systems (...

A novel endoscopic artificial intelligence system to assist in the diagnosis of autoimmune gastritis: a multicenter study.

Endoscopy
BACKGROUND:  Autoimmune gastritis (AIG), distinct from Helicobacter pylori-associated atrophic gastritis (HpAG), is underdiagnosed due to limited awareness. This multicenter study aimed to develop a novel endoscopic artificial intelligence (AI) syste...

Artificial intelligence for predicting treatment responses in autoimmune rheumatic diseases: advancements, challenges, and future perspectives.

Frontiers in immunology
Autoimmune rheumatic diseases (ARD) present a significant global health challenge characterized by a rising prevalence. These highly heterogeneous diseases involve complex pathophysiological mechanisms, leading to variable treatment efficacies across...