Clinical characteristics of COVID-19 in children and adolescents: insights from an Italian paediatric cohort using a machine-learning approach.

ABSTRACT:

Introduction

The epidemiology and clinical characteristics of COVID-19 evolved due to new SARS-CoV-2 variants of concern (VOCs). The Omicron VOC's higher transmissibility increased paediatric COVID-19 cases and hospital admissions. Most research during the Omicron period has focused on hospitalised cases, leaving a gap in understanding the disease's evolution in community settings. This study targets children with mild to moderate COVID-19 during pre-Omicron and Omicron periods. It aims to identify patterns in COVID-19 morbidity by clustering individuals based on symptom similarities and duration of symptoms and develop a machine-learning tool to classify new cases into risk groups.

Methods

We propose a data-driven approach to explore changes in COVID-19 characteristics by a

SUBMITTER: Fiandrino S 

PROVIDER: S-EPMC12164349 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature