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Metabolomics, Microbiomics, Machine learning during the COVID-19 pandemic.
Bardanzellu, Flaminia; Fanos, Vassilios.
Afiliación
  • Bardanzellu F; Neonatal Intensive Care Unit, Department of Surgical Sciences, AOU University of Cagliari, Cagliari, Italy.
  • Fanos V; Neonatal Intensive Care Unit, Department of Surgical Sciences, AOU University of Cagliari, Cagliari, Italy.
Pediatr Allergy Immunol ; 33 Suppl 27: 86-88, 2022 01.
Article en En | MEDLINE | ID: mdl-35080309
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.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Prognostic_studies / Risk_factors_studies / Screening_studies Límite: Humans Idioma: En Revista: Pediatr Allergy Immunol Asunto de la revista: ALERGIA E IMUNOLOGIA / PEDIATRIA Año: 2022 Tipo del documento: Article País de afiliación: Italia

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Prognostic_studies / Risk_factors_studies / Screening_studies Límite: Humans Idioma: En Revista: Pediatr Allergy Immunol Asunto de la revista: ALERGIA E IMUNOLOGIA / PEDIATRIA Año: 2022 Tipo del documento: Article País de afiliación: Italia