Dermatology

Atopy

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

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Dermatology Subcategories: Atopy Psoriasis
Showing 64-84 of 3,566 articles
InterDIA: Interpretable prediction of drug-induced autoimmunity through ensemble machine learning approaches.

Drug-induced autoimmunity (DIA) is a non-IgE immune-related adverse drug reaction that poses substan...

Machine learning models for preventative mobile health asthma control.

INTRODUCTION: Asthma attacks are set off by triggers such as pollutants from the environment, respir...

Assessing ChatGPT's accuracy and reliability in asthma general knowledge: implications for artificial intelligence use in public health education.

BACKGROUND: Integrating Artificial Intelligence (AI) into public health education represents a pivot...

Machine learning-derived asthma and allergy trajectories in children: a systematic review and meta-analysis.

INTRODUCTION: Numerous studies have characterised trajectories of asthma and allergy in children usi...

Bioequivalence study of fluticasone propionate nebuliser suspensions in healthy Chinese subjects.

BACKGROUND: Fluticasone propionate is a synthetic trifluoro-substituted glucocorticoid, a highly sel...

Machine learning analysis of CD4+ T cell gene expression in diverse diseases: insights from cancer, metabolic, respiratory, and digestive disorders.

CD4 T cells play a pivotal role in the immune system, particularly in adaptive immunity, by orchestr...

Artificial intelligence in pediatric allergy research.

UNLABELLED: Atopic dermatitis, food allergy, allergic rhinitis, and asthma are among the most common...

Serum Vitamin D Profiles of Children with Asthma in Southwest Saudi: A Comparative Cross-Sectional Study.

BACKGROUND: Evidence suggests a strong association between vitamin D status and asthma, with individ...

Milk ladder: Who? When? How? Where? with the lowest risk of reaction.

The milk ladder (ML) approach, which is the gradual reintroduction of the milk allergen from the lea...

Accurate Airway Tree Segmentation in CT Scans via Anatomy-Aware Multi-Class Segmentation and Topology-Guided Iterative Learning.

Intrathoracic airway segmentation in computed tomography is a prerequisite for various respiratory d...

Predicting Asthma Exacerbations Using Machine Learning Models.

INTRODUCTION: Although clinical, functional, and biomarker data predict asthma exacerbations, newer ...

Predicting paediatric asthma exacerbations with machine learning: a systematic review with meta-analysis.

BACKGROUND: Asthma exacerbations in children pose a significant burden on healthcare systems and fam...

Identification of TXN and F5 as novel diagnostic gene biomarkers of the severe asthma based on bioinformatics and machine learning analysis.

Asthma poses a major threat to human health. The aim of this study was to identify genetic markers o...

Assessing prospective molecular biomarkers and functional pathways in severe asthma based on a machine learning method and bioinformatics analyses.

BACKGROUND: Severe asthma, which differs significantly from typical asthma, involves specific molecu...

A preliminary review of the utility of artificial intelligence to detect eosinophilic chronic rhinosinusitis.

While typically diagnosed with biopsy, ECRS may be predicted preoperatively with the use of AI. Vari...

Graph neural networks in multi-stained pathological imaging: extended comparative analysis of Radiomic features.

PURPOSE: This study investigates the application of Radiomic features within graph neural networks (...

Tracing the path from preschool wheezing to asthma.

This short review illustrates, using two recent studies, the potential and challenges of using machi...

Development and validation of machine learning models for diagnosis and prognosis of lung adenocarcinoma, and immune infiltration analysis.

The aim of our study was to develop robust diagnostic and prognostic models for lung adenocarcinoma ...

Quantitative characterization of eosinophilia in nasal polyps with AI-based single cell classification.

Eosinophilic granulocytes have characteristic morphological features. This makes them prime candidat...

PPG2RespNet: a deep learning model for respirational signal synthesis and monitoring from photoplethysmography (PPG) signal.

Breathing conditions affect a wide range of people, including those with respiratory issues like ast...

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