Asthma

Novel Machine Learning Identifies 5 Asthma Phenotypes Using Cluster Analysis of Real-World Data.

BACKGROUND: Asthma classification into different subphenotypes is important to guide personalized therapy and improve outcomes.

Exploiting protein language models for the precise classification of ion channels and ion transporters.

This study introduces TooT-PLM-ionCT, a comprehensive framework that consolidates three distinct systems, each meticulously tailored for one of the following tasks: distinguishing ion channels (ICs) from membrane proteins (MPs), segregating ion transporters (ITs) from MPs, and differentiating ICs from ITs. Drawing upon the strengths of six Protein Language Models (PLMs)-ProtBERT, ProtBERT-BFD, ESM...

Leveraging AI and Machine Learning to Develop and Evaluate a Contextualized User-Friendly Cough Audio Classifier for Detecting Respiratory Diseases: Protocol for a Diagnostic Study in Rural Tanzania.

BACKGROUND: Respiratory diseases, including active tuberculosis (TB), asthma, and chronic obstructive pulmonary disease (COPD), constitute substantial...

Identification of shared potential diagnostic markers in asthma and depression through bioinformatics analysis and machine learning.

BACKGROUND: There is mounting evidence that asthma might exacerbate depression. We sought to examine candidates for diagnostic genes in patients suffe...

Ultra-sensitive analysis of exhaled biomarkers in ozone-exposed mice via PAI-TOFMS assisted with machine learning algorithms.

Ground-level ozone ranks sixth among common air pollutants. It worsens lung diseases like asthma, emphysema, and chronic bronchitis. Despite recent at...

Novel 3D-based deep learning for classification of acute exacerbation of idiopathic pulmonary fibrosis using high-resolution CT.

PURPOSE: Acute exacerbation of idiopathic pulmonary fibrosis (AE-IPF) is the primary cause of death in patients with IPF, characterised by diffuse, bi...

Visual Outcomes after Suprasellar Meningioma Resection: A Retrospective Cohort Study and a Machine Learning-Based Predictive Model.

 In this research, the authors provide a retrospective cohort study of 82 patients with suprasellar meningiomas to identify predictors of the visual ...

An Accelerometer-Based Wearable Patch for Robust Respiratory Rate and Wheeze Detection Using Deep Learning.

Wheezing is a critical indicator of various respiratory conditions, including asthma and chronic obstructive pulmonary disease (COPD). Current diagnos...

A machine-learning exploration of the exposome from preconception in early childhood atopic eczema, rhinitis and wheeze development.

BACKGROUND: Most previous research on the environmental epidemiology of childhood atopic eczema, rhinitis and wheeze is limited in the scope of risk f...

[Feeling analysis on allergen immunotherapy on using an unsupervised machine learning model].

OBJECTIVE: Analyze feelings about allergen-specific immunotherapy on using the VADER model VADER () model.

Demystification of artificial intelligence for respiratory clinicians managing patients with obstructive lung diseases.

INTRODUCTION: Asthma and chronic obstructive pulmonary disease (COPD) are leading causes of morbidity and mortality worldwide. Despite all available d...

Hyperpolarized Gas Imaging in Lung Diseases: Functional and Artificial Intelligence Perspective.

Pathophysiologic changes in lung diseases are often accompanied by changes in ventilation and gas exchange. Comprehensive evaluation of lung function ...

Early prediction of pediatric asthma in the Canadian Healthy Infant Longitudinal Development (CHILD) birth cohort using machine learning.

BACKGROUND: Early identification of children at risk of asthma can have significant clinical implications for effective intervention and treatment. Th...

Analysis of the improvement effect of Astragalus extract on oxidative stress injury in viral myocarditis through STAT3/IL-6.

The objective of this study was to investigate the improvement effect of Astragalus (AS) extract on oxidative stress (OS) and inflammatory response of...

Inclusion complex of turmeric essential oil with hydroxypropyl-β-cyclodextrin: Preparation, characterization and release kinetics.

The application of turmeric essential oil (TEO), a natural effective antibacterial agent, in food preservation is limited due to high volatility and l...

Towards Personalised Mood Prediction and Explanation for Depression from Biophysical Data.

Digital health applications using Artificial Intelligence (AI) are a promising opportunity to address the widening gap between available resources and...

potently inhibits the activity of SARS-CoV-2 3CL protease.

The ongoing coronavirus infectious disease (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) still urgently r...

Mechanistic analysis of Th2-type inflammatory factors in asthma.

BACKGROUND: The main pathological features of asthma are widespread chronic inflammation of the airways and restricted ventilation due to airway remod...

Improved antimicrobial activities of essential oils nanoencapsulated into hydroxypropyl-beta-cyclodextrins.

Natural antimicrobials have recently gained increasing interest over synthetic antimicrobials to overcome foodborne pathogens and food microbial conta...

Effect of Disinfection Method and Testing Methodology on the Performance of a Breath-Enhanced Jet Nebulizer.

National guidelines for cystic fibrosis recommend cleaning and disinfecting nebulizers after each use. We tested two groups of five reusable breath-en...