{"title":"Future Perspectives for Artificial Intelligence in Allergy: Advances in Diagnosis, Monitoring, and Personalized Care.","authors":"Esther Moreno, Vidal Moreno, Belén Curto, Ignacio Dávila","doi":"10.18176/jiaci.1154","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":50173,"journal":{"name":"Journal of Investigational Allergology and Clinical Immunology","volume":" ","pages":"85-99"},"PeriodicalIF":6.6000,"publicationDate":"2026-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Investigational Allergology and Clinical Immunology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.18176/jiaci.1154","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/3/10 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ALLERGY","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
The Journal of Investigational Allergology and Clinical Immunology (J Investig Allergol Clin Immunol) provides an attractive and very active forum for basic and clinical research in allergology and clinical immunology.Journal of Investigational Allergology and Clinical Immunology publishes original works, reviews, short communications and opinions.