Alberto Tozzi · Machine learning clinical decision support systems for surveillance: a case study on pertussis and RSV in children.
Article1 min read·Published Oct 2026

Machine learning clinical decision support systems for surveillance: a case study on pertussis and RSV in children.

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Article · Oct 2026 · 1 min read

In brief

In brief

This study evaluates a machine learning algorithm that uses clinical signs and symptoms to diagnose RSV infection and pertussis in infants under one year old. The system aims to improve diagnostic accuracy in emergency settings while providing real-time data for public health surveillance of respiratory infections.

Written by the GCMD Library team from the article.

Alberto Tozzi

We tested the performance of a machine learning (ML) algorithm based on signs and symptoms for the diagnosis of RSV infection or pertussis in the first year of age to support clinical decisions and provide timely data for public health surveillance. We used data from a retrospective case series of children in the first year of life investigated for acute respiratory infections in the emergency roo…

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