AIMC Topic: Neonatal Sepsis
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Machine Learning Models as Early Warning Systems for Neonatal Infection.
Clinics in perinatology
Nov 27, 2024
Neonatal infections pose a significant threat to the health of newborns. Associated morbidity and mortality risks underscore the urgency of prompt diagnosis and treatment with appropriate empiric antibiotics. Delay in treatment can be fatal; thus, ea...
A machine learning-based electronic nose for detecting neonatal sepsis: Analysis of volatile organic compound biomarkers in fecal samples.
Clinica chimica acta; international journal of clinical chemistry
Sep 24, 2024
BACKGROUND: Neonatal sepsis is a global health threat, contributing to high morbidity and mortality rates among newborns. Recognizing the profound impact of neonatal sepsis on long-term health outcomes emphasizes the critical need for timely detectio...
Distinguishing neonatal culture-negative sepsis from rule-out sepsis with artificial intelligence-derived graphs.
Pediatric research
Aug 15, 2024
Novel artificial intelligence methods can aide in identification of cases of conditions using only unstructured electronic health record data. This graph-based method compares comprehensive electronic health records among neonates using temporal data...
Diagnostic Performance of Machine Learning-based Models in Neonatal Sepsis: A Systematic Review.
The Pediatric infectious disease journal
Jul 26, 2024
BACKGROUND: Timely diagnosis of neonatal sepsis is challenging. We aimed to systematically evaluate the diagnostic performance of sophisticated machine learning (ML) techniques for the prediction of neonatal sepsis.
Optimal use of β-lactams in neonates: machine learning-based clinical decision support system.
EBioMedicine
Jun 24, 2024
BACKGROUND: Accurate prediction of the optimal dose for β-lactam antibiotics in neonatal sepsis is challenging. We aimed to evaluate whether a reliable clinical decision support system (CDSS) based on machine learning (ML) can assist clinicians in ma...
Machine Learning: A Potential Therapeutic Tool to Facilitate Neonatal Therapeutic Decision Making.
Paediatric drugs
Jun 16, 2024
Bacterial infection is one of the major causes of neonatal morbidity and mortality worldwide. Finding rapid and reliable methods for early recognition and diagnosis of bacterial infections and early individualization of antibacterial drug administrat...
Early detection of late-onset neonatal sepsis from noninvasive biosignals using deep learning: A multicenter prospective development and validation study.
International journal of medical informatics
Feb 4, 2024
BACKGROUND: Neonatal sepsis is responsible for significant morbidity and mortality worldwide. Its accurate and timely diagnosis is hindered by vague symptoms and the urgent necessity for early antibiotic intervention. The gold standard for diagnosing...
Aiding clinical assessment of neonatal sepsis using hematological analyzer data with machine learning techniques.
International journal of laboratory hematology
May 4, 2021
INTRODUCTION: Early diagnosis and antibiotic administration are essential for reducing sepsis morbidity and mortality; however, diagnosis remains difficult due to complex pathogenesis and presentation. We created a machine learning model for bacteria...
Machine Learning to Support Hemodynamic Intervention in the Neonatal Intensive Care Unit.
Clinics in perinatology
May 20, 2020
Hemodynamic support in neonatal intensive care is directed at maintaining cardiovascular wellbeing. At present, monitoring of vital signs plays an essential role in augmenting care in a reactive manner. By applying machine learning techniques, a mode...
Endocan serum concentration in uninfected newborn infants.
Journal of infection in developing countries
Sep 30, 2019
INTRODUCTION: Endocan is a specific endothelial mediator involved in the inflammatory response. Its role in the diagnosis of sepsis has been studied in adult patients and late onset neonatal sepsis. The clinical signs of early onset sepsis (EOS) are ...
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