Pulmonology

Asthma

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

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Showing 43-63 of 1,587 articles
Analysis of the sensitization activity of leaves protein.

The determination of allergenic proteins in leaves, which is the main components of immune activity...

Assessing the Clinical and Functional Status of COPD Patients Using Speech Analysis During and After Exacerbation.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) affects breathing, speech production, and c...

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...

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...

Development of machine learning models for the prediction of the skin sensitization potential of cosmetic compounds.

BACKGROUND: To enhance the accuracy of allergen detection in cosmetic compounds, we developed a co-c...

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...

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...

Alg-MFDL: A multi-feature deep learning framework for allergenic proteins prediction.

The escalating global incidence of allergy patients illustrates the growing impact of allergic issue...

Future of allergy and immunology: Is artificial intelligence the key in the digital era?

Artificial intelligence (AI) is reshaping allergy and immunology by integrating cutting-edge technol...

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...

Tracing the path from preschool wheezing to asthma.

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

Employing a synergistic bioinformatics and machine learning framework to elucidate biomarkers associating asthma with pyrimidine metabolism genes.

BACKGROUND: Asthma, a prevalent chronic inflammatory disorder, is shaped by a multifaceted interplay...

Machine learning-derived phenotypic trajectories of asthma and allergy in children and adolescents: protocol for a systematic review.

INTRODUCTION: Development of asthma and allergies in childhood/adolescence commonly follows a sequen...

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