Current state and prospects of artificial intelligence in allergy.
artificial intelligence
deep learning
diagnosis
machine learning
precision medicine
Journal
Allergy
ISSN: 1398-9995
Titre abrégé: Allergy
Pays: Denmark
ID NLM: 7804028
Informations de publication
Date de publication:
10 2023
10 2023
Historique:
revised:
08
07
2023
received:
20
04
2023
accepted:
31
07
2023
medline:
2
10
2023
pubmed:
16
8
2023
entrez:
16
8
2023
Statut:
ppublish
Résumé
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.
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
2623-2643Informations de copyright
© 2023 The Authors. Allergy published by European Academy of Allergy and Clinical Immunology and John Wiley & Sons Ltd.
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