Allergy & Immunology

HLAIImaster: a deep learning method with adaptive domain knowledge predicts HLA II neoepitope immunogenic responses.

While significant strides have been made in predicting neoepitopes that trigger autologous CD4+ T ce...

SPIN: sex-specific and pathway-based interpretable neural network for sexual dimorphism analysis.

Sexual dimorphism in prevalence, severity and genetic susceptibility exists for most common diseases...

Identification of disease-specific genes related to immune infiltration in nonalcoholic steatohepatitis using machine learning algorithms.

To identify disease signature genes associated with immune infiltration in nonalcoholic steatohepati...

Machine Learning Links T-cell Function and Spatial Localization to Neoadjuvant Immunotherapy and Clinical Outcome in Pancreatic Cancer.

Tumor molecular data sets are becoming increasingly complex, making it nearly impossible for humans ...

Machine Learning for Clinical Decision Support of Acute Streptococcal Pharyngitis: A Pilot Study.

BACKGROUND: Group A Streptococcus (GAS) is the predominant bacterial pathogen of pharyngitis in chil...

Automatic pterygopalatine fossa segmentation and localisation based on DenseASPP.

BACKGROUND: Allergic rhinitis constitutes a widespread health concern, with traditional treatments o...

How Can Artificial Intelligence Help With Management of Allergic Conditions?

Advanced Technologies in Radiation Research.

The U.S. Government is committed to maintaining a robust research program that supports a portfolio ...

[CHARACTERIZATION OF THE ADAPTIVE IMMUNE REPERTOIRE USING NEXT GENERATION SEQUENCING: RECENT DISCOVERIES IN THE FIELD OF PRIMARY IMMUNODEFICIENCY, AND THE UPCOMING FUTURE].

A powerful adaptive immune system, which includes cellular (T lymphocytes) and humoral (B lymphocyte...

Artificial intelligence and allergic rhinitis: does ChatGPT increase or impair the knowledge?

BACKGROUND: Optimal management of allergic rhinitis requires patient education with easy access to a...

Automatically pre-screening patients for the rare disease aromatic l-amino acid decarboxylase deficiency using knowledge engineering, natural language processing, and machine learning on a large EHR population.

OBJECTIVES: Electronic health record (EHR) data may facilitate the identification of rare diseases i...

Harnessing artificial intelligence for advancing early diagnosis in hidradenitis suppurativa.

This perspective delves into the integration of artificial intelligence (AI) to enhance early diagno...

Weakly Supervised Deep Learning Predicts Immunotherapy Response in Solid Tumors Based on PD-L1 Expression.

UNLABELLED: Programmed death-ligand 1 (PD-L1) IHC is the most commonly used biomarker for immunother...

The Human Phenotype Ontology in 2024: phenotypes around the world.

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defi...

Stratum corneum nanotexture feature detection using deep learning and spatial analysis: a noninvasive tool for skin barrier assessment.

BACKGROUND: Corneocyte surface nanoscale topography (nanotexture) has recently emerged as a potentia...

Deep Learning-based Time-to-event Analysis of Depression and Asthma using the All of Us Research Program.

While there is a growing recognition of the association between depression and asthma, few studies h...

Predicting Immune Checkpoint Inhibitor-Related Pneumonitis via Computed Tomography and Whole-Lung Analysis Deep Learning.

BACKGROUND: Immune checkpoint inhibitor-related pneumonitis (ICI-P) is a fatal adverse event of immu...

Artificial Intelligence and Family Medicine.

Artificial intelligence (AI) is certainly going to have a large, potentially huge, impact on the pra...

Machine learning approaches for asthma disease prediction among adults in Sri Lanka.

Addressing the challenge of cost-effective asthma diagnosis amidst diverse symptom patterns among p...

[CLINICAL APPLICATION OF ARTIFICIAL INTELLIGENCE ON AUXILIARY DIAGNOSIS OF ADULT ASTHMA].

Fuzzy-Based Bioengineering System for Predicting and Diagnosing Diseases of the Nervous System Triggered by the Interaction of Industrial Frequency Electromagnetic Fields.

The study aims to enhance the standard of medical care for individuals working in the electric power...