Header image

PARALLEL SESSION 10 - INFECTION 1

Tracks
SOFIA
Wednesday, October 22, 2025
4:00 PM - 6:00 PM

Overview

Machine Learning and Artificial Intelligence to detect patient deterioratiom


Details

Moderators: Christoph Schwarz, Germany and Rob Taal, The Netherlands

16:00 - 16:30
External validation of a Machine Learning Model for neonatal sepsis
Janno Schouten, The Netherlands

16:30 - 17:00
Developing and Implementing AI based clinical decision support for early detection of sepsis. lessons learned
Eric Giannoni, Switzerland

17.00 – 17.15 513
Individualised duration of antibiotic treatment in culture-negative early-onset infection in term-born newborns (DurATi-n): A nationwide randomised controlled non-inferiority trial in Denmark. Emma Malchau Carlsen (Denmark)

17.15 – 17.30 633
Risk Factors and Early Predictors of Mortality in Early-Onset Neonatal Sepsis Varvara Dimopoulou (Switzerland)

17.15 – 17.30 624
Causative organisms of early-onset neonatal sepsis in Uganda raise the suspicion of hospital-acquired infection Sarah Sturrock (United Kingdom)

17.45 - 18.00 96
Probiotic Organisms in the Neonatal Intensive Care Unit Michael Meyer (New Zealand)


Speaker

Dr. Varvara Dimopoulou
Doctor
Clinic of Neonatology, Department Mother-Woman-Child, Lausanne University Hospital, Switzerland

Risk Factors and Early Predictors of Mortality in Early-Onset Neonatal Sepsis

Dr. Emma Malchau Carlsen
Doctor
Rigshospitalet

Individualised duration of antibiotic treatment in culture-negative early-onset infection in term-born newborns (DurATi-n): A nationwide randomised controlled non-inferiority trial in Denmark.

Prof. Michael Meyer
Doctor
Middlemore Hospital

Probiotic Organisms in the Neonatal Intensive Care Unit

Dr. Sarah Sturrock
Doctor
City St George's, University Of London

Causative organisms of early-onset neonatal sepsis in Uganda raise the suspicion of hospital-acquired infection

loading