AI Medical Compendium Topic:
Infant

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Deep convolutional neural networks for multi-modality isointense infant brain image segmentation.

NeuroImage
The segmentation of infant brain tissue images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) plays an important role in studying early brain development in health and disease. In the isointense stage (approximately 6-8 month...

Assessment of paediatric thoracic robotic surgery.

Interactive cardiovascular and thoracic surgery
OBJECTIVES: Many studies have reported that robotic-assisted surgery is safe and feasible for paediatric cases. However, very few paediatric thoracic robotic cases have been described. The aim of this study was to share our preliminary experience wit...

Multi-institutional review of outcomes of robot-assisted laparoscopic extravesical ureteral reimplantation.

The Journal of urology
PURPOSE: We performed a multi-institutional assessment of the outcomes and complications of robot-assisted laparoscopic extravesical ureteral reimplantation for vesicoureteral reflux in children.

Machine learning-based approaches for distinguishing viral and bacterial pneumonia in paediatrics: A scoping review.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Pneumonia is the leading cause of hospitalisation and mortality among children under five, particularly in low-resource settings. Accurate differentiation between viral and bacterial pneumonia is essential for guiding approp...

High-frequency monitoring enables machine learning-based forecasting of acute child malnutrition for early warning.

Proceedings of the National Academy of Sciences of the United States of America
The number of acutely food insecure people worldwide has doubled since 2017, increasing demand for early warning systems (EWS) that can predict food emergencies. Advances in computational methods, and the growing availability of near-real time remote...

Integrative machine learning identifies robust inflammation-related diagnostic biomarkers and stratifies immune-heterogeneous subtypes in Kawasaki disease.

Pediatric rheumatology online journal
BACKGROUND: Kawasaki disease (KD), a pediatric systemic vasculitis, lacks reliable diagnostic biomarkers and exhibits immune heterogeneity, complicating clinical management. Current therapies face challenges in targeting specific immune pathways and ...

Using Machine Learning to Identify Predictors of Maternal and Infant Hair Cortisol Concentration Before and During the COVID-19 Pandemic.

Stress and health : journal of the International Society for the Investigation of Stress
Hair cortisol concentration (HCC) has been theorized to reflect chronic stress, and maternal and infant HCC may be correlated due to shared genetic, physiological, behavioural, and environmental factors, such as stressful life circumstances. The curr...

Diagnostic Stewardship of Blood Cultures in the Pediatric ICU Using Machine Learning.

Hospital pediatrics
OBJECTIVE: The medical community recently experienced a severe shortage of blood culture media bottles. Rates of blood stream infection (BSI) among critically ill children are low. We sought to design a machine learning (ML) model able to identify ch...

Machine Learning for Predicting Waitlist Mortality in Pediatric Heart Transplantation.

Pediatric transplantation
BACKGROUND: Waitlist mortality remains a critical issue for pediatric heart transplant (HTx) candidates, particularly for candidates with congenital heart disease. Listing center organ offer acceptance practices have been identified as a factor influ...