AIMC Topic: Gestational Age
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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...
Machine learning approaches for predicting fetal macrosomia at different stages of pregnancy: a retrospective study in China.
BMC pregnancy and childbirth
Feb 11, 2025
BACKGROUND: Macrosomia presents significant risks to both maternal and neonatal health, however, accurate antenatal prediction remains a major challenge. This study aimed to develop machine learning approaches to enhance the prediction of fetal macro...
Longitudinal twin growth discordance patterns and adverse perinatal outcomes.
American journal of obstetrics and gynecology
Jan 7, 2025
BACKGROUND: Growth discordance in twin pregnancies is associated with increased perinatal morbidity and mortality, yet the patterns of discordance progression and the utility of Doppler assessments remain underinvestigated.
Predicting preterm birth using electronic medical records from multiple prenatal visits.
BMC pregnancy and childbirth
Dec 21, 2024
This study aimed to predict preterm birth in nulliparous women using machine learning and easily accessible variables from prenatal visits. Elastic net regularized logistic regression models were developed and evaluated using 5-fold cross-validation ...
Adult
Sensitivity and Specificity
Ultrasonography, Prenatal
Prenatal Care
Predictive Value of Tests
Area Under Curve
Gestational Age
Risk Assessment
Logistic Models
Female
Infant, Newborn
Premature Birth
Young Adult
Humans
Machine Learning
Electronic Health Records
Pregnancy
Cervical Length Measurement
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...
Development of a machine learning model for prediction of intraventricular hemorrhage in premature neonates.
Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery
Dec 16, 2024
PURPOSE: Intraventricular hemorrhage (IVH) is a common and severe complication in premature neonates, leading to long-term neurological impairments. Early prediction and identification of risk factors for IVH in premature neonates are crucial for imp...
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.
Prediction of fetal brain gestational age using multihead attention with Xception.
Computers in biology and medicine
Sep 14, 2024
Accurate gestational age (GA) prediction is crucial for monitoring fetal development and ensuring optimal prenatal care. Traditional methods often face challenges in terms of precision and prediction efficiency. In this context, leveraging modern dee...
Mobil Monitoring Doppler Ultrasound (MoMDUS) study: protocol for a prospective, observational study investigating the use of artificial intelligence and low-cost Doppler ultrasound for the automated quantification of hypertension, pre-eclampsia and fetal growth restriction in rural Guatemala.
BMJ open
Sep 10, 2024
INTRODUCTION: Undetected high-risk conditions in pregnancy are a leading cause of perinatal mortality in low-income and middle-income countries. A key contributor to adverse perinatal outcomes in these settings is limited access to high-quality scree...
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