EAACI guidelines on environmental science in allergic diseases and asthma - Leveraging artificial intelligence and machine learning to develop a causality model in exposomics
Author(s)
Type
Journal Article
Abstract
Allergic diseases and asthma are intrinsically linked to the environment we live in and to patterns of exposure. The integrated approach to understanding the effects of exposures on the immune system includes the ongoing collection of large-scale and complex data. This requires sophisticated methods to take full advantage of what this data can offer. Here we discuss the progress and further promise of applying artificial intelligence and machine-learning approaches to help unlock the power of complex environmental data sets toward providing causality models of exposure and intervention. We discuss a range of relevant machine-learning paradigms and models including the way such models are trained and validated together with examples of machine learning applied to allergic disease in the context of specific environmental exposures as well as attempts to tie these environmental data streams to the full representative exposome. We also discuss the promise of artificial intelligence in personalized medicine and the methodological approaches to healthcare with the final AI to improve public health.
Date Issued
2023-07
Date Acceptance
2023-02-01
Citation
Allergy, 2023, 78 (7), pp.1742-1757
ISSN
0105-4538
Publisher
Wiley
Start Page
1742
End Page
1757
Journal / Book Title
Allergy
Volume
78
Issue
7
Copyright Statement
© 2023 European Academy of Allergy and Clinical Immunology and John Wiley & Sons Ltd. This is the peer reviewed version of the following article: Shamji, MH, Ollert, M, Adcock, IM, et al. EAACI guidelines on environmental science in allergic diseases and asthma – Leveraging artificial intelligence and machine learning to develop a causality model in exposomics. Allergy. 2023; 78: 1742-1757, which has been published in final form at https://doi.org/10.1111/all.15667 This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.
Identifier
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000935500700001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
allergy
Allergy
ANTIGEN
artificial intelligence
asthma
environment
exposome
Immunology
Life Sciences & Biomedicine
PREDICTION
Science & Technology
SKIN BARRIER
Publication Status
Published
Date Publish Online
2023-02-05