AIMC Topic: Infant, Newborn

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Methodological conduct and risk of bias in studies on prenatal birthweight prediction models using machine learning techniques: a systematic review.

BMC pregnancy and childbirth Jul 2, 2025
OBJECTIVE: To assess the methodological quality and the risk of bias, of studies that developed prediction models using Machine Learning (ML) techniques to estimate prenatal birthweight.
Bias Birth Weight Fetal Weight Pregnancy Female Infant, Newborn Reproducibility of Results Humans Machine Learning Research Design
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Listening deeper: neural networks unravel acoustic features in preterm infant crying.

Scientific reports Jul 2, 2025
Early infant crying provides critical insights into neurodevelopment, with atypical acoustic features linked to conditions such as preterm birth. However, previous studies have focused on limited and specific acoustic features, hindering a more compr...
Gestational Age Crying Acoustics Sound Spectrography Infant, Premature Humans Neural Networks, Computer Female Infant, Newborn Male
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Dual smart sensor data-based deep learning network for premature infant hypoglycemia detection.

Scientific reports Jul 2, 2025
In general, deficient birth weight neonates suffer from hypoglycemia, and this can be quite disadvantageous. Like oxygen, glucose is a building block of life and constitutes the significant share of energy produced by the fetus and the neonate during...
Humans Algorithms Photoplethysmography Monitoring, Physiologic Hypoglycemia Infant, Premature Female Infant, Newborn Deep Learning Blood Glucose
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Potential use of saliva infrared spectra and machine learning for a minimally invasive screening test for congenital syphilis in infants.

Scientific reports Jul 1, 2025
Congenital syphilis is a global public health issue, and its diagnostic complexity poses a challenge to early treatment. Fourier Transform Infrared Spectroscopy (FTIR) is a promising technological tool that facilitates the detection and diagnosis of ...
Humans Machine Learning Female Spectroscopy, Fourier Transform Infrared Principal Component Analysis Saliva Syphilis, Congenital Infant, Newborn Sensitivity and Specificity Male Infant
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Mortality risk associated with clinical signs of possible serious bacterial infection (PSBI) in young infants in Africa and Asia: protocol for a secondary pooled analysis.

BMJ open Jun 24, 2025
INTRODUCTION: The WHO's Integrated Management of Childhood Illness (IMCI) in young infants <2 months of age includes the identification and management of signs of possible serious bacterial infection (PSBI). However, equal importance is given to all ...
Humans Research Design Female Infant, Newborn Bacterial Infections Infant Mortality Asia Risk Factors Infant Africa
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Machine learning model for the prediction of postoperative acute kidney injury (AKI) in neonates undergoing digestive surgery.

Pediatric surgery international Jun 24, 2025
OBJECTIVE: The aim of our study is to determine the main predictors of postoperative AKI in neonates using machine learning models compared with the logistic regression model.
Machine Learning Digestive System Surgical Procedures Incidence Retrospective Studies Logistic Models Acute Kidney Injury Predictive Value of Tests Female Infant, Newborn Humans Risk Factors Male Postoperative Complications
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The early prediction of neonatal necrotizing enterocolitis in high-risk newborns based on two medical center clinical databases.

The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians Jun 23, 2025
: Early identification and timely preventive interventions play an essential role for improving the prognosis of newborns with necrotizing enterocolitis (NEC). Thus, establishing a novel and simple prediction model is of great clinical significance. ...
Enterocolitis, Necrotizing ROC Curve Logistic Models Early Diagnosis Prognosis Retrospective Studies Female Infant, Newborn Risk Factors Male Case-Control Studies Humans Machine Learning Databases, Factual
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Development of Machine Learning-Based Risk Prediction Models to Predict Rapid Weight Gain in Infants: Analysis of Seven Cohorts.

JMIR public health and surveillance Jun 18, 2025
BACKGROUND: Rapid weight gain (RWG) during infancy, defined as an upward crossing of one centile line on a weight growth chart, is highly predictive of subsequent obesity risk. Identification of infant RWG could facilitate obesity risk assessment fro...
Male Risk Assessment Infant Cohort Studies Australia Humans Machine Learning New Zealand Female Weight Gain Infant, Newborn
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A Machine Learning-Based Clustering Analysis to Explore Bisphenol A and Phthalate Exposure from Medical Devices in Infants with Congenital Heart Defects.

Environmental health perspectives Jun 18, 2025
BACKGROUND: Plastic-containing medical devices are commonly used in critical care units and other patient care settings. Patients are often exposed to xenobiotic agents that are leached out from plastic-containing medical devices, including bisphenol...
Phthalic Acids Machine Learning Heart Defects, Congenital Environmental Pollutants Humans Female Infant Bisphenol A Compounds Environmental Exposure Cluster Analysis Infant, Newborn Equipment and Supplies Phenols Male Benzhydryl Compounds
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Identifying determinants of under-5 mortality in Bangladesh: A machine learning approach with BDHS 2022 data.

PloS one Jun 11, 2025
BACKGROUND: Under-5 mortality in Bangladesh remains a critical indicator of public health and socio-economic development. Traditional methods often struggle to capture the complex, non-linear relationships influencing under-5 mortality. This study le...
Infant Child, Preschool Female Child Mortality Health Surveys Infant, Newborn Humans Infant Mortality Adult Machine Learning Bangladesh Male Algorithms
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