AIMC Topic: Infant, Newborn
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Machine learning prediction of preterm birth in women under 35 using routine biomarkers in a retrospective cohort study.
Scientific reports
Mar 25, 2025
Preterm birth (PTB), defined as delivery before 37 weeks, affects 15 million infants annually, accounting for 11% of live births and over 35% of neonatal deaths. While advanced maternal age (≥ 35 years) is a known risk factor, PTB risk in women under...
Early prediction of intraventricular hemorrhage in very low birth weight infants using deep neural networks with attention in low-resource settings.
Scientific reports
Mar 24, 2025
Early prediction of intraventricular hemorrhage (IVH) in very low-birthweight infants (VLBWIs) remains challenging because of multifactorial risk factors. IVH often occurs within a few hours after birth, yet its onset cannot be reliably predicted usi...
Machine learning-based prediction of vesicoureteral reflux outcomes in infants under antibiotic prophylaxis.
Scientific reports
Mar 22, 2025
We aimed to investigate the independent outcome predictors of continuous antibiotic prophylaxis (CAP) in vesicoureteral reflux, train a model to predict the outcome, and evaluate which infants should be referred for endoscopic vesicoureteral reflux c...
Predicting low birth weight risks in pregnant women in Brazil using machine learning algorithms: data from the Araraquara cohort study.
BMC pregnancy and childbirth
Mar 19, 2025
BACKGROUND: Low birth weight (LBW) is a critical factor linked to neonatal morbidity and mortality. Early prediction is essential for timely interventions. This study aimed to develop and evaluate predictive models for LBW using machine learning algo...
Predicting infant brain connectivity with federated multi-trajectory GNNs using scarce data.
Medical image analysis
Mar 13, 2025
The understanding of the convoluted evolution of infant brain networks during the first postnatal year is pivotal for identifying the dynamics of early brain connectivity development. Thanks to the valuable insights into the brain's anatomy, existing...
Do Treatment Choices by Artificial Intelligence Correspond to Reality? Retrospective Comparative Research with Necrotizing Enterocolitis as a Use Case.
Medical decision making : an international journal of the Society for Medical Decision Making
Mar 12, 2025
BackgroundIn cases of surgical necrotizing enterocolitis (NEC), the choice between laparotomy (LAP) or comfort care (CC) presents a complex, ethical dilemma. A behavioral artificial intelligence technology (BAIT) decision aid was trained on expert kn...
A machine learning approach to predict mortality and neonatal persistent pulmonary hypertension in newborns with congenital diaphragmatic hernia. A retrospective observational cohort study.
European journal of pediatrics
Mar 11, 2025
UNLABELLED: Congenital diaphragmatic hernia (CDH) has high morbidity and mortality rates. This study aimed to develop a machine learning (ML) algorithm to predict outcomes based on prenatal and early postnatal data. This retrospective observational c...
Proposing a machine learning-based model for predicting nonreassuring fetal heart.
Scientific reports
Mar 6, 2025
The capacity to forecast nonreassuring fetal heart (NFH) is essential for minimizing perinatal complications; therefore, this research aims to establish if a machine learning (ML) model can predict NFH. This was a retrospective analysis of informatio...
Retinal Vascularization Rate Predicts Retinopathy of Prematurity and Remains Unaffected by Low-Dose Bevacizumab Treatment.
American journal of ophthalmology
Mar 5, 2025
PURPOSE: To assess the rate of retinal vascularization derived from ultra-widefield (UWF) imaging-based retinopathy of prematurity (ROP) screening as predictor of type 1 ROP and characterize the effect of anti-vascular endothelial growth factor (anti...
Exploring the achievements and forecasting of SDG 3 using machine learning algorithms: Bangladesh perspective.
PloS one
Mar 4, 2025
BACKGROUND: Sustainable Development Goal 3 (SDG 3), focusing on ensuring healthy lives and well-being for all, holds global significance and is particularly vital for Bangladesh. Neonatal Mortality Rate (NMR), Under-5 Mortality Rate (U5MR), Maternal ...
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