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Artificial intelligence and wheezing in children: where are we now?
Laura Venditto1,2, Sonia Morano2, Michele Piazza2
1Cystic Fibrosis Center of Verona, Azienda Ospedaliera Universitaria Integrata, Verona, Italy.
Frontiers in Medicine
|September 11, 2024
Summary
Artificial Intelligence (AI) and Machine Learning (ML) offer new ways to manage childhood wheezing. These technologies aid in early recognition, risk assessment, and predicting asthma in preschoolers, improving care and reducing costs.
Area of Science:
- Pediatric Pulmonology and Allergology
- Artificial Intelligence in Healthcare
- Machine Learning Applications
Background:
- Recurrent wheezing affects up to one-third of preschoolers, impacting quality of life and healthcare resources.
- The COVID-19 pandemic has increased healthcare workload and necessitated reduced hospital access.
- There is a growing need for innovative solutions in managing childhood respiratory conditions.
Purpose of the Study:
- To review recent advancements in Artificial Intelligence (AI) applications for childhood wheezing.
- To summarize evidence on AI/ML in wheezing recognition, diagnosis, phenotyping, and asthma prediction.
- To provide an overview of AI-driven home monitoring and tele-management strategies.
Main Methods:
- Review of current literature on AI and Machine Learning (ML) in pediatric wheezing.
- Analysis of AI applications including AI-augmented stethoscopes and smartphone monitoring.
- Discussion of ML algorithms for wheezing phenotyping and asthma prediction.
Main Results:
- AI and ML are increasingly used for disease recognition, risk stratification, and decision support in pediatric pulmonology.
- AI-powered tools can enhance early recognition and monitoring of preschool wheezing.
- ML algorithms have shown promise in wheezing phenotyping and predicting asthma development in young children.
Conclusions:
- AI and ML approaches can significantly improve the management of preschool wheezing, aiding in recognition, diagnosis, and prediction.
- Tele-management and home monitoring tools powered by AI can reduce economic and social costs associated with childhood wheezing.
- Continued research and application of AI/ML are crucial for advancing pediatric respiratory care and asthma prevention.
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