Pulmonology

Asthma

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

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Non-invasive acoustic classification of adult asthma using an XGBoost model with vocal biomarkers.

Traditional diagnostic methods for asthma, a widespread chronic respiratory illness, are often limit...

Why Protein Modifications Matter for Digestibility: The Case of Ara h 1 Peanut Allergen and Trypsin Cleavage.

Trypsin is the principal intestinal endopeptidase and proteomics digestion tool, yet the impact of p...

Association between long-term exposure of polystyrene microplastics and exacerbation of seizure symptoms: Evidence from multiple approaches.

Microplastics are tiny plastic particles originating from both commercial product manufacturing and ...

Unsupervised identification of asthma symptom subtypes supports treatable traits approach.

BACKGROUND: Heterogeneity of asthma requires a personalized therapeutic approach. However, objective...

Investigation of key ferroptosis-associated genes and potential therapeutic drugs for asthma based on machine learning and regression models.

Bronchial asthma is a complex and heterogeneous disease, with ferroptosis, a form of non-apoptotic c...

HERGAI: an artificial intelligence tool for structure-based prediction of hERG inhibitors.

The human Ether-à-go-go-Related Gene (hERG) potassium channel is crucial for repolarizing the cardia...

Artificial intelligence in smartphone video analysis for equine asthma diagnostic support.

BACKGROUND: Equine asthma is a prevalent respiratory disease that negatively impacts horses' health ...

iALP: Identification of Allergenic Proteins Based on Large Language Model and Gate Linear Unit.

The rising incidence of allergic disorders has emerged as a pressing public health issue worldwide, ...

Artificial Intelligence Performance in Pediatric Asthma.

OBJECTIVE: Asthma is the most common chronic disease of childhood, characterized by symptoms such as...

Automated detection of air trapping from mechanical ventilation waveform through interpretable dual-channel 1D convolutional neural network.

. Air trapping is a major symptom of respiratory diseases like chronic obstructive pulmonary disease...

Anoikis-related biomarkers PARP1 and SDCBP as diagnostic and therapeutic targets for asthma.

This study aims to explore the association between anoikis-related genes (ARGs) and asthma. The data...

Predicting SARS-CoV-2-specific CD4 and CD8 T-cell responses elicited by inactivated vaccines in healthy adults using machine learning models.

The ongoing evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants highl...

Identifying and characterising asthma subgroups at high risk of severe exacerbations using machine learning and longitudinal real-world data.

OBJECTIVES: To identify and characterise distinct subgroups of patients with asthma with severe acut...

Machine learning-based prediction of celiac antibody seropositivity by biochemical test parameters.

The diagnostic delay in celiac disease (CD) is currently a burden for individual and society. Bioche...

A real-world data analysis of montelukast in FDA Adverse Event Reporting System (FAERS) database.

BACKGROUND: Montelukast(MTK) is a leukotriene receptor antagonist widely used clinically for treatin...

Biologics for severe asthma: deciphering what is best for the patient.

INTRODUCTION: Choosing the right biologic for the right patient is challenging. It requires evaluati...

Breath profiles in paediatric allergic asthma by proton transfer reaction mass spectrometry.

INTRODUCTION: Enhancing paediatric asthma diagnosis is crucial. Molecular analysis of exhaled breath...

A Machine Learning Analysis of Physiological Monitoring Signals to Detect Small Airway Narrowing Due to Cold Air Exposure in Asthma.

Asthma is a chronic inflammatory disease of the small airways, affecting over 200 million people glo...

From dairy to plant products: Understanding their structural fingerprints with X-rays.

Global interest in milk alternatives increases rapidly due to health awareness, their allergen-frien...

Machine learning-based model for acute asthma exacerbation detection using routine blood parameters.

BACKGROUND: Acute asthma exacerbations (AAEs) are a leading cause of asthma-related morbidity and mo...

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