Current state and prospects of artificial intelligence in allergy

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.

Automated summary

The field of medicine is increasingly interested in artificial intelligence (AI), which allows for new research questions and analysis of larger and different types of data. However, there are few applications of AI in the field of allergy that go beyond proof of concepts and provide clinical value. This review provides an understanding of AI concepts, discusses limitations and challenges such as data availability and bias, and explores potential directions to overcome them. It also presents case examples of AI applications in allergy, with a focus on diagnosis and subtyping. The review shares guidelines for good AI practice, prospects for field advancement, and initiatives to increase clinical impact, highlighting the potential of AI in deepening our understanding of disease mechanisms and contributing to precision medicine in allergy.