AIMC Topic: Pregnancy

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Artificial intelligence in in-vitro fertilization (IVF): A new era of precision and personalization in fertility treatments.

Journal of gynecology obstetrics and human reproduction Dec 27, 2024
In-vitro fertilization (IVF) has been a transformative advancement in assisted reproductive technology. However, success rates remain suboptimal, with only about one-third of cycles resulting in pregnancy and fewer leading to live births. This narrat...
Humans Ovulation Induction Artificial Intelligence Machine Learning Precision Medicine Pregnancy Female Male Deep Learning Fertilization in Vitro
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Latent representation learning for classification of the Doppler ultrasound images.

Computers in biology and medicine Dec 26, 2024
The classification of Doppler ultrasound images plays an important role in the diagnosis of pregnancy. However, it is a challenging problem that suffers from a variable length of these images with a dimension gap between them. In this study, we propo...
Pregnancy Female Ultrasonography, Prenatal Deep Learning Humans Ultrasonography, Doppler Image Processing, Computer-Assisted Algorithms Databases, Factual
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StUdy of Gestational diabetes And Risk using Electronic Data (SUGARED): a population-based cohort study-study protocol.

BMJ open Dec 26, 2024
INTRODUCTION: The incidence of gestational diabetes mellitus (GDM) in Australia has tripled in the last 20 years. Consequently, over 40 000 pregnancies are now diagnosed as 'higher risk' each year. This has increased antenatal surveillance and obstet...
New South Wales Hospitals, Public Pregnancy Routinely Collected Health Data Female Predictive Learning Models Risk Assessment Incidence Pregnancy Outcome Information Storage and Retrieval Humans Propensity Score Research Design Delivery, Obstetric Retrospective Studies Multilevel Analysis Logistic Models Observational Studies as Topic Diabetes, Gestational Glucose Tolerance Test
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Trajectory of breastfeeding among Chinese women and risk prediction models based on machine learning: a cohort study.

BMC pregnancy and childbirth Dec 24, 2024
BACKGROUND: Breastfeeding is the optimal source of nutrition for infants and young children, essential for their healthy growth and development. However, a gap in cohort studies tracking breastfeeding up to six months postpartum may lead caregivers t...
Humans Machine Learning Prospective Studies Pregnancy Female Breast Feeding Postpartum Period Infant, Newborn Young Adult Adult Risk Assessment Infant China Surveys and Questionnaires Cohort Studies East Asian People
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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...
Placenta Growth Factor Cohort Studies Pregnancy Trimester, First Pre-Eclampsia Humans Pregnancy Trimester, Second Machine Learning Risk Factors Prospective Studies Adult Biomarkers Risk Assessment Pregnancy Severity of Illness Index Female Parity
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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 ...
Risk Assessment Logistic Models Predictive Value of Tests Area Under Curve Gestational Age Adult Sensitivity and Specificity Ultrasonography, Prenatal Prenatal Care Cervical Length Measurement Humans Machine Learning Electronic Health Records Pregnancy Female Infant, Newborn Premature Birth Young Adult
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Identification of hub genes, diagnostic model, and immune infiltration in preeclampsia by integrated bioinformatics analysis and machine learning.

BMC pregnancy and childbirth Dec 21, 2024
PURPOSE: This study aimed to identify novel biomarkers for preeclampsia (PE) diagnosis by integrating Weighted Gene Co-expression Network Analysis (WGCNA) with machine learning techniques.
Pregnancy Female Adult Gene Expression Profiling Gene Regulatory Networks Humans Machine Learning Biomarkers Computational Biology Nomograms Databases, Genetic Pre-Eclampsia
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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...
Gestational Age Stillbirth Chorion Premature Birth Risk Factors Adult Pregnancy Outcome Logistic Models Humans Birth Weight Machine Learning Abortion, Spontaneous Pregnancy Hematoma Female Pregnancy Complications Infant, Newborn
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NMF typing and machine learning algorithm-based exploration of preeclampsia-related mechanisms on ferroptosis signature genes.

Cell biology and toxicology Dec 21, 2024
BACKGROUND: Globally, pre-eclampsia (PE) poses a major threat to the health and survival of pregnant women and fetuses, contributing significantly to morbidity and mortality. Recent studies suggest a pathological link between PE and ferroptosis. We a...
Machine Learning Algorithms Pregnancy Female Animals Humans Rats, Sprague-Dawley Cluster Analysis Ferroptosis Placenta Pre-Eclampsia Gene Expression Profiling Gene Regulatory Networks Rats Databases, Genetic
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Readability, quality and accuracy of generative artificial intelligence chatbots for commonly asked questions about labor epidurals: a comparison of ChatGPT and Bard.

International journal of obstetric anesthesia Dec 20, 2024
INTRODUCTION: Over 90% of pregnant women and 76% expectant fathers search for pregnancy health information. We examined readability, accuracy and quality of answers to common obstetric anesthesia questions from the popular generative artificial intel...
Generative Artificial Intelligence Humans Patient Education as Topic Artificial Intelligence Comprehension Pregnancy Health Literacy Female
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