From
Dr. Alberto Tozzi
Machine learning clinical decision support systems for surveillance: a case study on pertussis and RSV in children.
pubmed.ncbi.nlm.nih.gov shows its articles on its own site.
Read the article on pubmed.ncbi.nlm.nih.gov ↗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.
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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