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.

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

Fanos V.
Ultimo
2022-01-01

Abstract

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.
2022
OMICS technologies
SARS-CoV-2
biomarkers
machine learning
viral spread
Artificial Intelligence
Humans
Machine Learning
Metabolomics
Pandemics
SARS-CoV-2
COVID-19
File in questo prodotto:
File Dimensione Formato  
Pediatric Allergy Immunology - 2022 - Bardanzellu - Metabolomics Microbiomics Machine learning during the COVID‐19.pdf

accesso aperto

Tipologia: versione editoriale (VoR)
Dimensione 176.52 kB
Formato Adobe PDF
176.52 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/331180
Citazioni
  • ???jsp.display-item.citation.pmc??? 2
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 5
social impact