Artificial Intelligence in Asthma and COPD: Current Status and Future Potential.

Area of Science:

• Healthcare technology
• Medical informatics
• Respiratory medicine

Background:

• Chronic respiratory diseases, including asthma and COPD, are significant global health burdens.
• Artificial intelligence (AI), particularly machine learning and deep learning, offers potential for personalized care in lung diseases.
• Effective AI implementation requires large datasets and clinician trust.

Purpose of the Study:

• To review the current evidence on AI applications in managing asthma and COPD.
• To explore how AI can support diagnosis, phenotyping, risk stratification, and monitoring in chronic respiratory disorders.

Main Methods:

• A narrative literature review was conducted.
• Searches included ScienceDirect, PubMed, and Google Scholar for English-language studies.
• References of relevant articles were also screened.

Main Results:

• AI is being utilized across the asthma-COPD spectrum for diagnosis, phenotyping, and risk prediction.
• AI tools can enhance continuous monitoring using diverse data sources like clinical records and imaging.
• AI applications show potential in improving outcomes and personalized care for asthma and COPD patients.

Conclusions:

• AI-based tools can assist clinicians in diagnosing, phenotyping, and monitoring asthma and COPD.
• Robust validation, transparency, and governance are crucial for the safe and reliable implementation of AI in routine clinical practice.
• Ensuring patient safety and building trust are paramount for integrating AI into respiratory care.