By now, the advantages of artificial intelligence (AI) are apparent to nearly every industry, including health care. It’s no surprise that AI is transforming the landscape of disease management, including allergic diseases such as asthma, atopic dermatitis, food allergies, allergic rhinitis and urticaria. By leveraging techniques like reinforcement learning, machine learning, deep learning, and natural language processing, AI can analyze vast amounts of data to support doctors in disease prediction, diagnosis, treatment and management.
Chinese researchers examined AI’s use in managing asthma and outlined their findings in the study, “Application and Research Progress of Artificial Intelligence in Allergic Diseases,” which was recently published in the International Journal of Medical Sciences.
Key applications in asthma management:
- Diagnosis and classification: AI models can analyze cough and breathing sounds, electronic health records (EHR) and wearable sensor data to accurately diagnose asthma and classify its severity. For example, smartphone apps and advanced algorithms have shown high accuracy in diagnosing asthma based on cough sounds and breathing patterns.
- Treatment: AI helps optimize the use of asthma medications like glucocorticosteroids and bronchodilators. It can predict the efficacy of treatments, such as Allergen Immunotherapy (AIT), and assist in determining the duration of asthma biologics.
- Forecasting and management: AI tools can predict acute asthma attacks and hospital readmissions by analyzing environmental factors and patient data. Machine learning models can forecast emergency visits and outpatient numbers based on air quality, weather conditions and pollen counts.
Key advantages and limitations of AI:
- Advantages: AI offers precise, real-time monitoring and personalized treatment recommendations, improving patient outcomes and reducing health care costs. It also facilitates telemedicine, bridging gaps in medical resources globally.
- Limitations: Continuous data collection can be challenging in clinical settings, and AI models require extensive data storage and skilled professionals for effective implementation.
Researchers said AI’s integration into health care promises to revolutionize the management of allergic diseases, advancing respiratory care and improving the quality of life for millions affected by allergic diseases.
