Metabolomics, Microbiomics, Machine learning during the COVID-19 pandemic
Flaminia Bardanzellu1, Vassilios Fanos1
1Neonatal Intensive Care Unit, Department of Surgical Sciences, AOU University of Cagliari, Cagliari, Italy.
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.
More Related Videos
07:11Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
Published on: November 10, 2023
08:51Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
Published on: September 20, 2024
Related Concept Videos
MALDI-TOF Mass Spectrometry
Matrix-assisted laser desorption ionization (MALDI) is a commonly...
Genomics
Steps in Outbreak Investigation
Modern Molecular Taxonomy
Applications of Molecular Taxonomy
Proteomics
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
