# The Evolving Role of Artificial Intelligence in Pediatric Asthma Management: Opportunities and Challenges for Modern Healthcare

## TL;DR

Artificial intelligence is transforming pediatric asthma care by enabling early diagnosis, personalized treatment, and better disease management, though challenges like data privacy and dataset availability remain.

## Contribution

This paper reviews the opportunities and challenges of integrating AI and ML into pediatric asthma management, emphasizing the need for pediatric-specific solutions.

## Key findings

- AI tools can analyze clinical, genetic, and environmental data to identify asthma subtypes and predict exacerbations.
- Wearable devices and smart inhalers improve remote monitoring and medication adherence in children.
- Pediatric-specific datasets and transparent AI systems are critical for successful implementation in clinical settings.

## Abstract

Asthma is a common chronic disease in children, contributing to significant morbidity and healthcare utilization worldwide. The integration of artificial intelligence (AI) and machine learning (ML) into pediatric asthma care is rapidly advancing, offering new opportunities for early diagnosis, risk stratification, and personalized management. AI-driven tools can analyze complex clinical, genetic, and environmental data to identify asthma phenotypes and endotypes, predict exacerbations, and support timely interventions. In pediatric populations, these technologies enable non-invasive diagnostic approaches, remote monitoring through wearable devices, and improved medication adherence via smart inhalers and digital health platforms. Despite these advances, challenges remain, including the need for pediatric-specific datasets, transparency in AI decision-making, and careful attention to data privacy and equity. The integration of AI in pediatric asthma care and into the clinical decision system can offer personalized treatment plans, reducing the burden of the disease both for patients and health professionals. This is a narrative review on the applications of AI and ML in pediatric asthma care.