Background Asthma exacerbations in children pose a significant burden on healthcare
systems and families. While traditional risk assessment tools exist, artificial intelligence (AI) …

Abstract Background Machine Learning refers to a methodology in the domain of data
analytic that automates the systematic building of the model. It permits the discovery of …

The integration of artificial intelligence (AI) and machine learning (ML) has shown potential
for various applications in the medical field, particularly for diagnosing and managing …

Abstract Purpose of Review Artificial intelligence (AI), be it neuronal networks, machine
learning or deep learning, has numerous beneficial effects on healthcare systems; however …

Background The integration of machine learning (ML) in predicting asthma-related
outcomes in children presents a novel approach in pediatric health care. Objective This …

Objective Asthma is a leading cause of emergency department (ED) visits and
hospitalizations in children, though many could be prevented. Our study objective was to …

Asthma research and management needs to meet the priorities of the end user-patients,
carers and clinicians. A better understanding of the natural history of asthma and the …

Over the last few decades, globalization has driven up the demand for hospital Supply
Chain Management (SCM) with the goal of bio-medical development and improving …

Objective: To review pediatric artificial intelligence (AI) implementation studies from 2010-
2021 and analyze reported performance measures. Methods: We searched …

Background An early warning tool to predict attacks could enhance asthma management
and reduce the likelihood of serious consequences. Electronic health records (EHRs) …