AIMC Topic: Maternal Age

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Preterm birth trends and risk factors in a multi-ethnic Asian population: A retrospective study from 2017 to 2023, can we screen and predict this?

Annals of the Academy of Medicine, Singapore May 21, 2025
INTRODUCTION: Preterm birth (PTB) remains a leading cause of perinatal morbidity and mortality worldwide. Understanding Singapore's PTB trends and associated risk factors can inform effective strategies for screening and intervention. This study anal...
Humans Retrospective Studies Pregnancy Female Body Mass Index Singapore Asian People Ethnicity Gestational Age Maternal Age Infant, Newborn Premature Birth Risk Factors Adult Logistic Models
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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...
Maternal Age Infant, Newborn Premature Birth Risk Factors Adult Logistic Models Humans Machine Learning Biomarkers Retrospective Studies Pregnancy Female
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Machine learning algorithms in constructing prediction models for assisted reproductive technology (ART) related live birth outcomes.

Scientific reports Dec 30, 2024
Currently applicable models for predicting live birth outcomes in patients who received assisted reproductive technology (ART) have methodological or study design limitations that greatly obstruct their dissemination and application. Models suitable ...
Fertilization in Vitro Logistic Models Female Maternal Age Adult Reproductive Techniques, Assisted Humans Male Live Birth Machine Learning China Algorithms ROC Curve Retrospective Studies Pregnancy
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Predicting adverse pregnancy outcome in Rwanda using machine learning techniques.

PloS one Dec 5, 2024
BACKGROUND: Adverse pregnancy outcomes pose significant risk to maternal and neonatal health, contributing to morbidity, mortality, and long-term developmental challenges. This study aimed to predict these outcomes in Rwanda using supervised machine ...
Abortion, Spontaneous Pregnancy Complications Maternal Age Live Birth Stillbirth Cross-Sectional Studies Middle Aged Adolescent Humans Rwanda Pregnancy Outcome Machine Learning Pregnancy Female Risk Factors Young Adult Adult
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Geographic inequities in neonatal survival in Nigeria: a cross-sectional evidence from spatial and artificial neural network analyses.

Journal of biosocial science Sep 19, 2024
This study was conducted to provide empirical evidence of geographical variations of neonatal mortality and its associated social determinants with a view to improving neonatal survival at the subnational level in Nigeria. With a combination of spati...
Neural Networks, Computer Female Infant, Newborn Adult Cross-Sectional Studies Humans Infant Mortality Spatial Analysis Maternal Age Health Status Disparities Geography Birth Intervals Male Infant Nigeria Socioeconomic Factors Cluster Analysis
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Beyond black-box models: explainable AI for embryo ploidy prediction and patient-centric consultation.

Journal of assisted reproduction and genetics Jul 4, 2024
PURPOSE: To determine if an explainable artificial intelligence (XAI) model enhances the accuracy and transparency of predicting embryo ploidy status based on embryonic characteristics and clinical data.
Referral and Consultation Ploidies Maternal Age Preimplantation Diagnosis Humans Artificial Intelligence Machine Learning Retrospective Studies Pregnancy Female Adult Embryo Transfer Fertilization in Vitro Support Vector Machine Blastocyst
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An explainable machine learning-based clinical decision support system for prediction of gestational diabetes mellitus.

Scientific reports Jan 21, 2022
Gestational Diabetes Mellitus (GDM), a common pregnancy complication associated with many maternal and neonatal consequences, is increased in mothers with overweight and obesity. Interventions initiated early in pregnancy can reduce the rate of GDM i...
Humans Machine Learning Models, Statistical Randomized Controlled Trials as Topic Diabetes, Gestational Maternal Age ROC Curve Decision Support Systems, Clinical Pregnancy Smartphone Female Mobile Applications Risk Factors Overweight Adult Risk Assessment
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Machine learning approaches to predict gestational age in normal and complicated pregnancies via urinary metabolomics analysis.

Scientific reports Sep 7, 2021
The elucidation of dynamic metabolomic changes during gestation is particularly important for the development of methods to evaluate pregnancy status or achieve earlier detection of pregnancy-related complications. Some studies have constructed model...
Body Mass Index Metabolomics Models, Biological Japan Gas Chromatography-Mass Spectrometry Pregnancy Complications Gestational Age Maternal Age Hypertension, Pregnancy-Induced Pregnancy Female Humans Infant, Newborn Machine Learning Parity Prospective Studies Adult
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Pregnancy prediction performance of an annotation-free embryo scoring system on the basis of deep learning after single vitrified-warmed blastocyst transfer: a single-center large cohort retrospective study.

Fertility and sterility Jul 8, 2021
OBJECTIVE: To analyze the performance of an annotation-free embryo scoring system on the basis of deep learning for pregnancy prediction after single vitrified blastocyst transfer (SVBT) compared with the performance of other blastocyst grading syste...
Single Embryo Transfer Vitrification Adult Middle Aged Image Interpretation, Computer-Assisted Deep Learning Fertilization in Vitro Humans Heart Rate, Fetal Pregnancy Rate Retrospective Studies Treatment Outcome Maternal Age Cryopreservation Pregnancy Embryo Implantation Embryo Culture Techniques Female Predictive Value of Tests Time-Lapse Imaging Blastocyst Infertility
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Prediction of obstetrical and fetal complications using automated electronic health record data.

American journal of obstetrics and gynecology Oct 22, 2020
An increasing number of delivering women experience major morbidity and mortality. Limited work has been done on automated predictive models that could be used for prevention. Using only routinely collected obstetrical data, this study aimed to devel...
Obstetric Labor Complications Time Factors Female Blood Pressure Premature Birth Pre-Eclampsia Humans Hypoxia-Ischemia, Brain Parity Maternal Age Stillbirth Machine Learning Reproducibility of Results Postpartum Hemorrhage Retrospective Studies Clinical Decision Rules Adult Electronic Health Records Pregnancy in Obesity Pregnancy Routinely Collected Health Data Uterine Rupture
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