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AI Technology Enhances Early Prediction of Severe Asthma in Children

AI Technology Enhances Early Prediction of Severe Asthma in Children

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AI tools developed by Mayo Clinic enhance early prediction of severe asthma risks in young children, enabling personalized and preventive care strategies. These innovative models analyze health records to identify high-risk kids as early as age 3, aiming to reduce complications and improve outcomes.

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Recent advancements in artificial intelligence (AI) have led to the development of innovative tools capable of predicting the risk of severe asthma exacerbations and respiratory infections in young children. Researchers from Mayo Clinic have created AI-driven models that utilize machine learning and natural language processing to analyze electronic health records from over 22,000 children born between 1997 and 2016 in southeastern Minnesota.

These tools can identify children at high risk as early as age 3 by extracting detailed information from doctors' notes, including symptoms, family history, and laboratory markers indicative of allergic inflammation. By applying established diagnostic checklists such as the Predetermined Asthma Criteria and the Asthma Predictive Index, the AI models successfully pinpoint a subgroup of children with a higher likelihood of serious asthma flares, frequent pneumonia, influenza, and RSV infections.

Children identified as high-risk often exhibit a family history of asthma, eczema, and allergic conditions, alongside lab findings like elevated eosinophils and allergen-specific IgE. These findings suggest a distinct asthma subtype vulnerable to respiratory illnesses, enabling earlier intervention and targeted management.

This initiative aligns with Mayo Clinic's "preCure" strategy, aiming to prevent severe disease progression through early detection and personalized care. Future steps involve testing these AI tools across diverse populations and integrating biological data to refine asthma subtypes and treatment approaches. Additionally, research is underway to explore immune-modulating therapies using lab-grown organoids, with the goal of improving early detection and prevention of childhood asthma.

The advent of these AI technologies marks a significant shift towards precision medicine in pediatric asthma, moving from reactive treatment to proactive prevention, thereby reducing hospitalizations and improving quality of life for affected children.

Source: https://medicalxpress.com/news/2025-09-ai-tools-severe-asthma-young.html

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