Predicting COVID-19 severity in pediatric patients using machine learning: a comparative analysis of algorithms and ensemble methods

Predicting COVID-19 severity in pediatric patients using machine learning: a comparative analysis of algorithms and ensemble methods

Abstract COVID-19 has posed a significant global health challenge, affecting individuals across all age groups. While extensive research has focused on adults, pediatric patients exhibit distinct clinical characteristics that necessitate specialized predictive models for disease severity. Machine le...

Full description

Saved in:
Bibliographic Details
Main Authors: Babak Pourakbari, Setareh Mamishi, Sepideh Keshavarz Valian, Shima Mahmoudi, Reihaneh Hosseinpour Sadeghi, Mohammad Reza Abdolsalehi, Mahmoud Khodabandeh, Mohammad Farahmand
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
COVID-19
Pediatric patients
Machine learning
Severity prediction
Random forest
Ensemble model
Online Access:https://doi.org/10.1038/s41598-025-15366-1
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41598-025-15366-1

Similar Items