Infant mortality is a major public health issue that is rooted in the larger problem of socio-economic and healthcare disparities. Deep learning techniques were employed in this study to predict infant mortality using data gathered via 2019 Ethiopia ...
INTRODUCTION: Mother-infant skin-to-skin contact (SSC) improves developmental and cognitive outcomes in preterm infants. However, the effects of SSC on healthy term infants remain unclear. We aim to investigate the short-term and long-term impacts of...
BMC medical informatics and decision making
Oct 10, 2025
OBJECTIVE: To develop and evaluate machine learning models combined with survival analysis for predicting 7-, 14-, and 28-day mortality in critically ill children with acute kidney injury (AKI), identifying key predictors to guide risk stratification...
BACKGROUND: Neonatal Intrahepatic Cholestasis caused by Citrin Deficiency (NICCD) is an autosomal recessive disorder affecting the urea cycle and energy metabolism. Newborn screening (NBS) usually relies on elevated citrulline, but some patients have...
The Journal of neuroscience : the official journal of the Society for Neuroscience
Oct 8, 2025
Early structural and molecular development of the human cortex is extensively studied, but little is known about the development of neuronal activity across cortical regions. We used dense array electroencephalography recordings and a machine learnin...
The Cochrane database of systematic reviews
Oct 7, 2025
This is a protocol for a Cochrane Review (diagnostic). The objectives are as follows: To assess the diagnostic performance of AI-based algorithms in comparison to the established reference standard of clinical diagnosis labels for ROP. Secondary obje...
BACKGROUND: The use of artificial intelligence (AI) in health care has been steadily increasing for over 2 decades. Integrating AI into neonatal intensive care units (NICUs) has promise as it has the potential to reshape neonatal care and improve out...
Neonatal hyperbilirubinemia is a common clinical condition that, if not promptly and effectively managed, may lead to rare but severe neurodevelopmental complications. This review traces the historical progression of screening, diagnostic, and therap...
BACKGROUND: Neonatal sepsis is a major cause of morbidity and mortality in low-resource settings and accurate, context-appropriate diagnostic methods are urgently needed to improve clinical outcomes.
Electronic health records contain multimodal data that can inform clinical decisions but are often unsuited for advanced machine learning analyses due to lack of labeled data. Here, we present InfEHR, a framework to automatically compute clinical lik...
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