AIMC Topic: Birth Weight

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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.
Humans Machine Learning Reproducibility of Results Bias Birth Weight Fetal Weight Research Design Pregnancy Female Infant, Newborn
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Birth weight prediction using artificial intelligence-based placental assessment from macroscopic photo: a retrospective study.

Placenta Apr 23, 2025
BACKGROUND: This study aimed to predict newborn birth weight through multifactorial analysis of macroscopic placental images using artificial intelligence (AI).
Machine Learning Retrospective Studies Pregnancy Female Humans Artificial Intelligence Infant, Newborn Adult Birth Weight Placenta
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Prediction of retinopathy of prematurity development and treatment need with machine learning models.

BMC ophthalmology Apr 10, 2025
BACKGROUND: To evaluate the effectiveness of machine learning (ML) models in predicting the occurrence of retinopathy of prematurity (ROP) and treatment need.
Male Birth Weight Infant, Premature Neonatal Screening Retrospective Studies Female Infant, Newborn Gestational Age Retinopathy of Prematurity Humans Machine Learning
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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...
Infant, Very Low Birth Weight Birth Weight Gestational Age Cerebral Intraventricular Hemorrhage Humans Neural Networks, Computer Female Infant, Newborn Risk Factors Male Deep Learning Cerebral Hemorrhage
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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...
Bevacizumab Retinal Vessels Gestational Age Retinopathy of Prematurity Retinal Neovascularization Infant, Newborn Humans Birth Weight Male Retrospective Studies Angiogenesis Inhibitors Vascular Endothelial Growth Factor A Follow-Up Studies Female Infant, Premature Intravitreal Injections
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Prediction of clinical risk factors in pregnancy using optimized neural network scheme.

Placenta Mar 4, 2025
Women should be aware of prenancy related health issues. A user-friendly model is developed in which the patients can use as well as clinicians to determine the risks associated with foetal development inside the womb, birth weight, whose effects are...
Pregnancy Female Risk Factors Ultrasonography, Prenatal Birth Weight Fetal Weight Humans Neural Networks, Computer Algorithms
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Evaluation of Pregnancy Risks in Women with Subchorionic Hematoma Using Machine Learning Models.

Medical science monitor : international medical journal of experimental and clinical research Dec 21, 2024
BACKGROUND Subchorionic hematoma (SCH) can lead to blood accumulation and potentially affect pregnancy outcomes. Despite being a relatively common finding in early pregnancy, the effects of SCH on pregnancy outcomes such as miscarriage, stillbirth, a...
Pregnancy Female Infant, Newborn Premature Birth Risk Factors Adult Pregnancy Outcome Pregnancy Complications Birth Weight Logistic Models Humans Gestational Age Abortion, Spontaneous Machine Learning Stillbirth Hematoma Chorion
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Constructing small for gestational age prediction models: A retrospective machine learning study.

European journal of obstetrics, gynecology, and reproductive biology Nov 26, 2024
OBJECTIVE: To develop machine learning prediction models for small for gestational age with baseline characteristics and biochemical tests of various pregnancy stages individually and collectively and compare predictive performance.
Gestational Age Infant, Small for Gestational Age Infant, Newborn Adult Birth Weight Machine Learning Retrospective Studies Pregnancy Female Humans
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Predicting newborn birth outcomes with prenatal maternal health features and correlates in the United States: a machine learning approach using archival data.

BMC pregnancy and childbirth Sep 17, 2024
BACKGROUND: Newborns are shaped by prenatal maternal experiences. These include a pregnant person's physical health, prior pregnancy experiences, emotion regulation, and socially determined health markers. We used a series of machine learning models ...
Birth Weight Humans Pregnancy Outcome Female Machine Learning Cephalometry United States Infant, Newborn Pregnancy Maternal Health Fetal Development Adult Male
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Comparison of machine learning algorithms and multiple linear regression for live weight estimation of Akkaraman lambs.

Tropical animal health and production Sep 3, 2024
This study was designed to predict the post-weaning weights of Akkaraman lambs reared on different farms using multiple linear regression and machine learning algorithms. The effect of factors the age of the dam, gender, type of lambing, enterprise, ...
Male India Birth Weight Body Weight Algorithms Female Machine Learning Animals Sheep Linear Models Sheep, Domestic
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