Metabolomics, Microbiomics, Machine learning during the COVID-19 pandemic.
OMICS technologies
SARS-CoV-2
biomarkers
machine learning
viral spread
Journal
Pediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology
ISSN: 1399-3038
Titre abrégé: Pediatr Allergy Immunol
Pays: England
ID NLM: 9106718
Informations de publication
Date de publication:
01 2022
01 2022
Historique:
revised:
29
07
2021
received:
05
07
2021
accepted:
07
08
2021
entrez:
26
1
2022
pubmed:
27
1
2022
medline:
1
2
2022
Statut:
ppublish
Résumé
COVID-19 pandemic has a significant impact worldwide, from the point of view of public health, social, and economic aspects. The correct strategies of diagnosis and global management are still under debate. In the next future, we firmly believe that combining the so-called 3 M's (metabolomics, microbiomics, and machine learning [artificial intelligence]) will be the optimal, accurate tool for the early diagnosis of COVID-19 subjects, risk assessment and stratification, patient management, and decision-making. If the currently available preliminary data obtain further confirms, through future studies on larger samples, simple biomarkers will provide predictive models for data analysis and interpretation, allowing a step toward personalized holistic medicine.
Identifiants
pubmed: 35080309
doi: 10.1111/pai.13640
pmc: PMC9303466
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
86-88Informations de copyright
© 2022 The Authors. Pediatric Allergy and Immunology published by European Academy of Allergy and Clinical Immunology and John Wiley & Sons Ltd.
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