Latest AI and machine learning research in asthma for healthcare professionals.
This study explores the potential of explainable artificial intelligence to advance our understanding of allergen peptides in the context of dermatology and cosmetics. We present a hybrid deep learning framework that integrates Temporal Convolutional Networks (TCN) and stacked Long Short-Term Memory (LSTM) architectures, enhanced with Evolutionary Scale Modeling (ESM) embeddings, to decode allerge...
OBJECTIVE: Exposure to benzo(a)pyrene (BaP) negatively affects lung inflammation in patients with asthma. However, there is a lack of systematic research on the key mechanisms of BaP toxicity in asthma. METHODS: In this study, BaP target genes were predicted using ChEMBL, SEA, and PharmMapper, and asthma-related genes were retrieved from GeneCards, OMIM, and TTD. A protein-protein interaction netw...
Generative artificial intelligence (AI) is rapidly emerging as a valuable tool in medicine, with increasing use in asthma and allergy practice. Large ...
BACKGROUND: Equitable access to prescribed therapies remains challenging for older adults with chronic respiratory diseases (CRDs) in rural China. Liq...
Cough is a common and physiologically informative component of respiratory morbidity, but its potential for diagnosing and monitoring disease is not t...
BACKGROUND: Asthma is a clinically heterogeneous airway disorder characterized by complex interactions between environmental exposures, immune activat...
INTRODUCTION: The global prevalence of heart failure continues to increase, particularly in ageing populations. Many older patients receiving home-bas...
Early identification of children at risk for persistent asthma is challenging because preschool respiratory symptoms are heterogeneous and often overl...
BACKGROUND: Title and abstract screening is a labor-intensive stage of systematic reviews. Large language models (LLMs) can automate this process, but...
BACKGROUND: COPD remains a leading cause of global morbidity and mortality, with acute exacerbations driving disease progression and healthcare utilis...
Artificial intelligence (AI) is reshaping dermatology through diagnostic image analysis, clinical documentation, and patient communication tools. Howe...
Lipid transfer proteins (LTPs) are clinically relevant allergens widely present in plant-based foods, and their reliable detection in complex food mat...
Air pollution remains a critical environmental health challenge in Thailand, yet evidence linking high-resolution exposure to short-term respiratory h...
Food allergies affect over 220 million individuals worldwide and present increasing challenges due to complex food matrices and processing-induced pro...
OBJECTIVE: To develop and validate an interpretable multi-centre interictal EEG biomarker for distinguishing epilepsy from mimickers, addressing the c...
OBJECTIVES: Pediatric asthma exacerbations are a common emergent condition treated by prehospital emergency medical services (EMS). However, retrospec...
INTRODUCTION: Exacerbations, impaired health-related quality of life (HRQoL) and reduced exercise capacity increase the risk of hospitalisations and d...
Atopic dermatitis (AD) is the most common inflammatory skin disease and carries the highest disability-adjusted life-years burden, ranking 15th among ...
Artificial intelligence (AI) in environmental health science is revolutionizing data analysis and problem-solving approaches. These technologies facil...
The landscape of asthma management is undergoing significant transformation. This change is driven by several factors: deeper understanding of asthma ...