AIMC Topic: Infant, Low Birth Weight

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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...
Female Infant, Newborn Risk Factors Young Adult Humans Machine Learning Algorithms Pregnancy ROC Curve Longitudinal Studies Infant, Low Birth Weight Gestational Age Adult Risk Assessment Brazil Cohort Studies
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Utilization of tree-based machine learning models for predicting low birth weight cases.

BMC pregnancy and childbirth Feb 26, 2025
BACKGROUND: Low birth weight (LBW) is a health condition that affects over 20 million gestational outcomes worldwide. The current literature indicates that machine learning models have the potential to assist healthcare professionals in predicting LB...
Humans Machine Learning Pregnancy Female Infant, Newborn Adult Infant, Low Birth Weight
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Causal machine learning models for predicting low birth weight in midwife-led continuity care intervention in North Shoa Zone, Ethiopia.

BMC medical informatics and decision making Feb 7, 2025
BACKGROUND: Low birth weight (LBW) is a critical global health issue that affects infants disproportionately, particularly in developing countries. This study adopted causal machine learning (CML) algorithms for predicting LBW in newborns, drawing fr...
Infant, Newborn Young Adult Adult Prenatal Care Ethiopia Infant, Low Birth Weight Humans Continuity of Patient Care Machine Learning Midwifery Pregnancy Female
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Predicting adverse birth outcome among childbearing women in Sub-Saharan Africa: employing innovative machine learning techniques.

BMC public health Jul 29, 2024
BACKGROUND: Adverse birth outcomes, including preterm birth, low birth weight, and stillbirth, remain a major global health challenge, particularly in developing regions. Understanding the possible risk factors is crucial for designing effective inte...
Risk Factors Young Adult Adult Adolescent Pregnancy Female Infant, Newborn Premature Birth Pregnancy Outcome Africa South of the Sahara Infant, Low Birth Weight Stillbirth Humans Machine Learning
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Can oral microbiome predict low birth weight infant delivery?

Journal of dentistry Apr 27, 2024
OBJECTIVES: This study aimed to identify the oral microbiota factors contributing to low birth weight (LBW) in Chinese pregnant women and develop a prediction model using machine learning.
Saliva Microbiota Mouth Infant, Low Birth Weight Streptococcus Humans Leptotrichia Adult Machine Learning Case-Control Studies Prospective Studies Female China Biomarkers Infant, Newborn RNA, Ribosomal, 16S Pregnancy Risk Factors
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Predicting risks of low birth weight in Bangladesh with machine learning.

PloS one May 26, 2022
BACKGROUND AND OBJECTIVE: Low birth weight is one of the primary causes of child mortality and several diseases of future life in developing countries, especially in Southern Asia. The main objective of this study is to determine the risk factors of ...
Birth Weight Bangladesh Risk Factors Infant, Low Birth Weight Infant Humans Child Machine Learning Logistic Models Infant, Newborn
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Assistive Framework for Automatic Detection of All the Zones in Retinopathy of Prematurity Using Deep Learning.

Journal of digital imaging Jul 8, 2021
Retinopathy of prematurity (ROP) is a potentially blinding disorder seen in low birth weight preterm infants. In India, the burden of ROP is high, with nearly 200,000 premature infants at risk. Early detection through screening and treatment can prev...
Humans Infant, Newborn Deep Learning Retina Infant, Premature Infant, Low Birth Weight Retinopathy of Prematurity
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Automated detection of early-stage ROP using a deep convolutional neural network.

The British journal of ophthalmology Aug 23, 2020
BACKGROUND/AIM: To automatically detect and classify the early stages of retinopathy of prematurity (ROP) using a deep convolutional neural network (CNN).
Gestational Age Retinopathy of Prematurity Image Processing, Computer-Assisted Birth Weight Infant, Premature Infant, Low Birth Weight Male Female Diagnosis, Computer-Assisted Infant, Newborn ROC Curve Sensitivity and Specificity Humans Cross-Sectional Studies Neural Networks, Computer Algorithms Retrospective Studies
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Artificial Intelligence in Retinopathy of Prematurity Diagnosis.

Translational vision science & technology Feb 10, 2020
Retinopathy of prematurity (ROP) is a leading cause of childhood blindness worldwide. The diagnosis of ROP is subclassified by zone, stage, and plus disease, with each area demonstrating significant intra- and interexpert subjectivity and disagreemen...
Infant, Newborn Child Infant, Low Birth Weight Retinopathy of Prematurity Humans Artificial Intelligence
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A class of joint models for multivariate longitudinal measurements and a binary event.

Biometrics Jan 11, 2016
Predicting binary events such as newborns with large birthweight is important for obstetricians in their attempt to reduce both maternal and fetal morbidity and mortality. Such predictions have been a challenge in obstetric practice, where longitudin...
Pregnancy Outcome Female Norway Markov Chains Humans Infant, Newborn Longitudinal Studies Infant, Low Birth Weight Machine Learning Sweden Models, Statistical Gestational Age Pregnancy Ultrasonography Bayes Theorem Monte Carlo Method
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