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Current state and prospects of artificial intelligence in allergy
  • +6
  • Merlijn van Breugel,
  • Rudolf S. N. Fehrmann,
  • Marnix Bügel,
  • Faisal I. Rezwan,
  • John Holloway,
  • Martijn Nawijn,
  • Sara Fontanella,
  • A Custovic,
  • Gerard Koppelman
Merlijn van Breugel
Universitair Medisch Centrum Groningen Beatrix Kinderziekenhuis
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Rudolf S. N. Fehrmann
Universitair Medisch Centrum Groningen Afdeling Oncologie
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Marnix Bügel
MIcompany
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Faisal I. Rezwan
University of Southampton School of Human Development and Health
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John Holloway
University of Southampton School of Human Development and Health
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Martijn Nawijn
Universitair Medisch Centrum Groningen Groningen Research Institute for Asthma and COPD
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Sara Fontanella
Imperial College London National Heart and Lung Institute
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A Custovic
Imperial College London National Heart and Lung Institute
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Gerard Koppelman
Universitair Medisch Centrum Groningen Beatrix Kinderziekenhuis

Corresponding Author:[email protected]

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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 and immunology. 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.
20 Apr 2023Submitted to Allergy
21 Apr 2023Submission Checks Completed
21 Apr 2023Assigned to Editor
21 Apr 2023Review(s) Completed, Editorial Evaluation Pending
24 Apr 2023Reviewer(s) Assigned
09 May 2023Editorial Decision: Revise Minor
09 Jul 20231st Revision Received
10 Jul 2023Review(s) Completed, Editorial Evaluation Pending
10 Jul 2023Submission Checks Completed
10 Jul 2023Assigned to Editor
16 Jul 2023Reviewer(s) Assigned
31 Jul 2023Editorial Decision: Accept