Current state and prospects of artificial intelligence in allergy

Abstract

The field of medicine is witnessing an exponential growth of interest in artificial intelligence (AI), which enables new research questions and the analysis of larger and new types of data. Nevertheless, applications that go beyond proof of concepts and deliver clinical value remain rare, especially in the field of allergy. This narrative review provides a fundamental understanding of the core concepts of AI and critically discusses its limitations and open challenges, such as data availability and bias, along with potential directions to surmount them. We provide a conceptual framework to structure AI applications within this field and discuss forefront case examples. Most of these applications of AI and machine learning in allergy concern supervised learning and unsupervised clustering, with a strong emphasis on diagnosis and subtyping. A perspective is shared on guidelines for good AI practice to guide readers in applying it effectively and safely, along with prospects of field advancement and initiatives to increase clinical impact. We anticipate that AI can further deepen our knowledge of disease mechanisms and contribute to precision medicine in allergy.

APAAACI 2023 International Conference: the innovation revolution in allergy, asthma, and immunology

“…No device has been authorized that uses generative AI or AGI or is powered by large language models. Similar trends are observed in Conformité Européene-marked medical devices incorporating AI within the European Union [ 10 ]. More recently, AI has also been applied to allergy research in asthma, atopic dermatitis, rhinology, adverse reactions to drugs and vaccines, food allergy, anaphylaxis, urticaria, and eosinophilic gastrointestinal disorders [ 8 , 10 ].…”

“…Similar trends are observed in Conformité Européene-marked medical devices incorporating AI within the European Union [ 10 ]. More recently, AI has also been applied to allergy research in asthma, atopic dermatitis, rhinology, adverse reactions to drugs and vaccines, food allergy, anaphylaxis, urticaria, and eosinophilic gastrointestinal disorders [ 8 , 10 ]. In future, AI will improve our understanding of patient profiles, disease mechanisms, risk stratification, and precision diagnosis and aid in the management of allergic and immunologic disorders.…”