AIMC Topic: Asthma
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Breath profiles in paediatric allergic asthma by proton transfer reaction mass spectrometry.
BMJ open respiratory research
Jun 27, 2025
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...
Altered static and dynamic functional network connectivity and combined Machine learning in asthma.
Neuroscience
Apr 26, 2025
Asthma is a reversible disease characterized by airflow limitation and chronic airway inflammation. Previous neuroimaging studies have shown structural and functional abnormalities in the brains of individuals with asthma. However, earlier research h...
Development and validation of a machine learning risk prediction model for asthma attacks in adults in primary care.
NPJ primary care respiratory medicine
Apr 23, 2025
Primary care consultations provide an opportunity for patients and clinicians to assess asthma attack risk. Using a data-driven risk prediction tool with routinely collected health records may be an efficient way to aid promotion of effective self-ma...
Applications of machine learning approaches for pediatric asthma exacerbation management: a systematic review.
BMC medical informatics and decision making
Apr 18, 2025
BACKGROUND: Pediatric asthma is a common chronic respiratory disease worldwide, and its acute exacerbation events significantly impact children's health and quality of life. Machine learning, an advanced data analysis technique, has shown great poten...
Application and research progress of artificial intelligence in allergic diseases.
International journal of medical sciences
Apr 9, 2025
Artificial intelligence (AI), as a new technology that can assist or even replace some human functions, can collect and analyse large amounts of textual, visual and auditory data through techniques such as Reinforcement Learning, Machine Learning, De...
Resolving multi-image spatial lipidomic responses to inhaled toxicants by machine learning.
Nature communications
Mar 26, 2025
Regional responses to inhaled toxicants are essential to understand the pathogenesis of lung disease under exposure to air pollution. We evaluate the effect of combined allergen sensitization and ozone exposure on eliciting spatial differences in lip...
Factors associated with the development of severe asthma: A nationwide study (FINASTHMA).
Annals of allergy, asthma & immunology : official publication of the American College of Allergy, Asthma, & Immunology
Mar 9, 2025
BACKGROUND: Severe asthma presents a major challenge to health care and negatively affects the quality of life of patients. Understanding the factors predicting the development of severe asthma is limited.
Edge Computing System for Automatic Detection of Chronic Respiratory Diseases Using Audio Analysis.
Journal of medical systems
Mar 4, 2025
Chronic respiratory diseases affect people worldwide, but conventional diagnostic methods may not be accessible in remote locations far from population centers. Sounds from the human respiratory system have displayed potential in autonomously detecti...
Understanding the Engagement and Interaction of Superusers and Regular Users in UK Respiratory Online Health Communities: Deep Learning-Based Sentiment Analysis.
Journal of medical Internet research
Feb 13, 2025
BACKGROUND: Online health communities (OHCs) enable people with long-term conditions (LTCs) to exchange peer self-management experiential information, advice, and support. Engagement of "superusers," that is, highly active users, plays a key role in ...
Assessing the diagnostic accuracy of machine learning algorithms for identification of asthma in United States adults based on NHANES dataset.
Scientific reports
Feb 6, 2025
Asthma diagnosis poses challenges due to underreporting of symptoms, misdiagnoses, and limitations in existing diagnostic tests. Machine learning (ML) offers a promising avenue for addressing these challenges by leveraging demographic and clinical da...
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