AIMC Topic: Pregnancy Trimester, Second

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Machine learning for the prediction of spontaneous preterm birth using early second and third trimester maternal blood gene expression: A cautionary tale.

PloS one Jun 27, 2025
Spontaneous preterm birth (sPTB) remains a significant global health challenge and a leading cause of neonatal mortality and morbidity. Despite advancements in neonatal care, the prediction of sPTB remains elusive, in part due to complex etiologies a...
Humans Machine Learning Adult Cohort Studies ROC Curve Pregnancy Trimester, Second Pregnancy Trimester, Third Biomarkers Pregnancy Female Premature Birth
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A comprehensive and bias-free machine learning approach for risk prediction of preeclampsia with severe features in a nulliparous study cohort.

BMC pregnancy and childbirth Dec 24, 2024
Preeclampsia is one of the leading causes of maternal morbidity, with consequences during and after pregnancy. Because of its diverse clinical presentation, preeclampsia is an adverse pregnancy outcome that is uniquely challenging to predict and mana...
Pregnancy Trimester, Second Machine Learning Humans Placenta Growth Factor Prospective Studies Severity of Illness Index Risk Factors Female Biomarkers Cohort Studies Adult Parity Pregnancy Risk Assessment Pregnancy Trimester, First Pre-Eclampsia
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Building a machine learning-based risk prediction model for second-trimester miscarriage.

BMC pregnancy and childbirth Nov 9, 2024
BACKGROUND: Second-trimester miscarriage is a common adverse pregnancy outcome that imposes substantial economic and psychological pressures on both the physical and mental well-being of patients and their families. Currently, there is a scarcity of ...
Humans Machine Learning Retrospective Studies Risk Assessment Abortion, Spontaneous Pregnancy Trimester, Second Pregnancy Female Risk Factors Adult
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Deep learning to estimate gestational age from fly-to cineloop videos: A novel approach to ultrasound quality control.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics Jan 8, 2024
OBJECTIVE: Low-cost devices have made obstetric sonography possible in settings where it was previously unfeasible, but ensuring quality and consistency at scale remains a challenge. In the present study, we sought to create a tool to reduce substand...
Pregnancy Female Ultrasonography, Prenatal Deep Learning Humans Biometry Pregnancy Trimester, Third Quality Control Video Recording Pregnancy Trimester, Second Gestational Age
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Novelelectronic health records applied for prediction of pre-eclampsia: Machine-learning algorithms.

Pregnancy hypertension Oct 28, 2021
OBJECTIVE: To predict risk of pre-eclampsia (PE) in women using machine learning (ML) algorithms, based on electronic health records (EHR) collected at the early second trimester.
Risk Assessment Pre-Eclampsia Pregnancy Trimester, Second Humans Machine Learning Retrospective Studies Electronic Health Records Pregnancy Female Adult
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Prediction of preterm birth in nulliparous women using logistic regression and machine learning.

PloS one Jun 30, 2021
OBJECTIVE: To predict preterm birth in nulliparous women using logistic regression and machine learning.
Pregnancy Trimester, Second Ontario Logistic Models Area Under Curve Pregnancy Trimester, First Parity Young Adult Adult ROC Curve Pregnancy Female Premature Birth Machine Learning Retrospective Studies Humans
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Prediction model development of late-onset preeclampsia using machine learning-based methods.

PloS one Aug 23, 2019
Preeclampsia is one of the leading causes of maternal and fetal morbidity and mortality. Due to the lack of effective preventive measures, its prediction is essential to its prompt management. This study aimed to develop models using machine learning...
Adult Logistic Models Support Vector Machine Bayes Theorem Pregnancy Trimester, Second Gestational Age Pregnancy Trimester, Third Pre-Eclampsia Age of Onset Humans Machine Learning Pregnancy Female
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Semiautomatic Fetal Intelligent Navigation Echocardiography Has the Potential to Aid Cardiac Evaluations Even in Less Experienced Hands.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine Aug 14, 2019
OBJECTIVES: To investigate the interobserver and intraobserver variability and corresponding learning curve in a semiautomatic approach for a standardized assessment of the fetal heart (fetal intelligent navigation echocardiography [FINE]).
Heart Defects, Congenital Ultrasonography, Prenatal Humans Learning Curve Clinical Competence Artificial Intelligence Echocardiography, Four-Dimensional Observer Variation Pregnancy Pregnancy Trimester, Second Female
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Comparison of logistic regression with machine learning methods for the prediction of fetal growth abnormalities: a retrospective cohort study.

BMC pregnancy and childbirth Aug 15, 2018
BACKGROUND: While there is increasing interest in identifying pregnancies at risk for adverse outcome, existing prediction models have not adequately assessed population-based risks, and have been based on conventional regression methods. The objecti...
Infant, Small for Gestational Age Retrospective Studies Fetal Macrosomia Pregnancy Gestational Weight Gain Female Body Mass Index Nova Scotia Infant, Newborn Humans Smoking Young Adult Pregnancy Trimester, Second Neural Networks, Computer Adult Machine Learning Statistics as Topic Cohort Studies Fetal Development Logistic Models
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A metabolomics-based approach for non-invasive screening of fetal central nervous system anomalies.

Metabolomics : Official journal of the Metabolomic Society May 25, 2018
BACKGROUND: Central nervous system anomalies represent a wide range of congenital birth defects, with an incidence of approximately 1% of all births. They are currently diagnosed using ultrasound evaluation. However, there is strong need for a more a...
Pregnancy Trimester, Second Female Case-Control Studies Neonatal Screening Humans Infant, Newborn Pilot Projects Fetal Diseases Adult Prospective Studies Metabolome Fetus Prenatal Care Biomarkers Gas Chromatography-Mass Spectrometry Nervous System Malformations Pregnancy
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