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Metabolomics, Microbiomics, Machine learning during the COVID‐19 pandemic

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,...

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Detalles Bibliográficos
Autores principales: Bardanzellu, Flaminia, Fanos, Vassilios
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9303466/
https://www.ncbi.nlm.nih.gov/pubmed/35080309
http://dx.doi.org/10.1111/pai.13640
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author Bardanzellu, Flaminia
Fanos, Vassilios
author_facet Bardanzellu, Flaminia
Fanos, Vassilios
author_sort Bardanzellu, Flaminia
collection PubMed
description 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.
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spelling pubmed-93034662022-07-28 Metabolomics, Microbiomics, Machine learning during the COVID‐19 pandemic Bardanzellu, Flaminia Fanos, Vassilios Pediatr Allergy Immunol Special Issue: 2021 Update From The Italian Society Of Pediatric Allergy And Immunology 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. John Wiley and Sons Inc. 2022-01-25 2022-01 /pmc/articles/PMC9303466/ /pubmed/35080309 http://dx.doi.org/10.1111/pai.13640 Text en © 2022 The Authors. Pediatric Allergy and Immunology published by European Academy of Allergy and Clinical Immunology and John Wiley & Sons Ltd. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Special Issue: 2021 Update From The Italian Society Of Pediatric Allergy And Immunology
Bardanzellu, Flaminia
Fanos, Vassilios
Metabolomics, Microbiomics, Machine learning during the COVID‐19 pandemic
title Metabolomics, Microbiomics, Machine learning during the COVID‐19 pandemic
title_full Metabolomics, Microbiomics, Machine learning during the COVID‐19 pandemic
title_fullStr Metabolomics, Microbiomics, Machine learning during the COVID‐19 pandemic
title_full_unstemmed Metabolomics, Microbiomics, Machine learning during the COVID‐19 pandemic
title_short Metabolomics, Microbiomics, Machine learning during the COVID‐19 pandemic
title_sort metabolomics, microbiomics, machine learning during the covid‐19 pandemic
topic Special Issue: 2021 Update From The Italian Society Of Pediatric Allergy And Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9303466/
https://www.ncbi.nlm.nih.gov/pubmed/35080309
http://dx.doi.org/10.1111/pai.13640
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