Addressing the challenge of cost-effective asthma diagnosis amidst diverse symptom patterns among patients, this study aims to develop a machine learning-based asthma prediction tool for self-detection of asthma. Data from 6,665 participants in the...
BACKGROUND: Asthma, a prevalent chronic inflammatory disorder, is shaped by a multifaceted interplay between genetic susceptibilities and environmental exposures. Despite strides in deciphering its pathophysiological landscape, the intricate molecula...
INTRODUCTION: Development of asthma and allergies in childhood/adolescence commonly follows a sequential progression termed the 'atopic march'. Recent reports indicate, however, that these diseases are composed of multiple distinct phenotypes, with p...
BACKGROUND: The interpretation of lung sounds plays a crucial role in the appropriate diagnosis and management of pediatric asthma. Applying artificial intelligence (AI) to this task has the potential to better standardize assessment and may even imp...
European respiratory review : an official journal of the European Respiratory Society
39537241
BACKGROUND: Asthma exacerbations in children pose a significant burden on healthcare systems and families. While traditional risk assessment tools exist, artificial intelligence (AI) offers the potential for enhanced prediction models.
Asthma poses a major threat to human health. The aim of this study was to identify genetic markers of severe asthma and analyze the relationship between key genes and immune infiltration. Differentially expressed genes (DEGs) were first screened by d...
The Journal of asthma : official journal of the Association for the Care of Asthma
39392250
BACKGROUND: Severe asthma, which differs significantly from typical asthma, involves specific molecular biomarkers that enhance our understanding and diagnostic capabilities. The objective of this study is to assess the biological processes underlyin...
This short review illustrates, using two recent studies, the potential and challenges of using machine learning methods to identify phenotypes of wheezing and asthma from childhood onwards.