Artificial intelligence (AI) is significantly transforming the specialty of allergy by offering novel tools for diagnosis, risk prediction, disease monitoring, and personalized care. This narrative review comprehensively explores key advances in the application of AI techniques-expert systems, machine learning, deep learning, and natural language processing-across various allergic diseases such as asthma, anaphylaxis, atopic dermatitis, food allergy, allergic rhinitis, eosinophilic esophagitis, and drug hypersensitivity reactions. Despite these advancements, several challenges persist, including model interpretability, external validation, and ethical and regulatory barriers. Nonetheless, AI holds strong potential to enhance diagnostic efficiency, therapeutic precision, and patient outcomes. This review presents an updated perspective on the state of the art of AI in allergy, highlighting both its achievements and ongoing challenges.
Moreno et al. (Tue,) studied this question.