BACKGROUND: Asthma is a chronic inflammatory disorder that adversely affects the quality of life, particularly in older adults. The coexistence of depression in asthma patients complicates their management and exacerbates health outcomes. This study ...
BACKGROUND: Chronic allergic rhinitis and asthma syndrome (CARAS) is a comorbid inflammatory condition affecting both upper and lower airways, with limited treatment options. Artesunate (ART), a derivative of artemisinin, has shown anti-inflammatory ...
BACKGROUND: Asthma is a heterogeneous disease characterized by chronic airway inflammation and metabolic dysregulation. Recent studies highlight the role of glycolysis and oxidative phosphorylation (OXPHOS) imbalance in asthma pathogenesis, yet the u...
PURPOSE OF REVIEW: This review aims to explore an effective and scalable approach for early asthma detection using cough sounds. The main objective is to evaluate whether a multi-model deep learning fusion framework can improve diagnostic accuracy an...
Asthma is a frequent and long-lasting disorder associated with airway inflammation. The disease severity may lead to serious health concerns and even mortality. In this work, we propose a novel hybrid approach using machine learning models and simila...
Machine learning is a vital tool in advancing drug development by accurately predicting the physical, chemical, and biological properties of various compounds. This study utilizes MATLAB program-based algorithms to calculate topological indices and m...
Traditional diagnostic methods for asthma, a widespread chronic respiratory illness, are often limited by factors such as patient cooperation with spirometry. Non-invasive acoustic analysis using machine learning offers a promising alternative for ob...
This study aims to explore the association between anoikis-related genes (ARGs) and asthma. The dataset GSE143303 for asthma were sourced from the GEO database, while ARGs were retrieved from the Harmonizome web portal and the GeneCards database. Dif...
OBJECTIVES: To identify and characterise distinct subgroups of patients with asthma with severe acute exacerbations (AEs) by using a multistep clustering methodology that combines supervised and unsupervised machine learning.
INTRODUCTION: Enhancing paediatric asthma diagnosis is crucial. Molecular analysis of exhaled breath is a rapidly evolving field aimed at harnessing established and innovative technologies for clinical applications. This study evaluates the feasibili...
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