Current state and prospects of artificial intelligence in allergy

Merlijn van Breugel, Rudolf S. N. Fehrmann, Marnix Bügel, Faisal I. Rezwan, John W. Holloway, Martijn C. Nawijn, Sara Fontanella, Adnan Custovic, Gerard H. Koppelman*

*Corresponding author for this work

Research output: Contribution to journalReview Articlepeer-review

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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.
Original languageEnglish
Pages (from-to)2623-2643
Number of pages21
JournalAllergy
Volume78
Issue number10
Early online date16 Aug 2023
DOIs
Publication statusPublished - 30 Sept 2023

Keywords

  • Artificial Intelligence
  • Humans
  • Hypersensitivity/diagnosis
  • Machine Learning
  • Precision Medicine

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