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Pregnancy

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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
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...

NMF typing and machine learning algorithm-based exploration of preeclampsia-related mechanisms on ferroptosis signature genes.

Cell biology and toxicology
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...

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
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...

Automated approach for fetal and maternal health management using light gradient boosting model with SHAP explainable AI.

Frontiers in public health
Fetal health holds paramount importance in prenatal care and obstetrics, as it directly impacts the wellbeing of mother and fetus. Monitoring fetal health through pregnancy is crucial for identifying and addressing potential risks and complications t...

Cost-effectiveness analysis of AI-based image quality control for perinatal ultrasound screening.

BMC medical education
PURPOSE: This study aimed to compare the cost-effectiveness of AI-based approaches with manual approaches in ultrasound image quality control (QC).

Leveraging machine learning models for anemia severity detection among pregnant women following ANC: Ethiopian context.

BMC public health
BACKGROUND: Anemia during pregnancy is a significant public health concern, particularly in resource-limited settings. Machine learning (ML) offers promising avenues for improved anemia detection and management. This study investigates the potential ...

Novel neural network classification of maternal fetal ultrasound planes through optimized feature selection.

BMC medical imaging
Ultrasound (US) imaging is an essential diagnostic technique in prenatal care, enabling enhanced surveillance of fetal growth and development. Fetal ultrasonography standard planes are crucial for evaluating fetal development parameters and detecting...

Predicting maternal risk level using machine learning models.

BMC pregnancy and childbirth
BACKGROUND: Maternal morbidity and mortality remain critical health concerns globally. As a result, reducing the maternal mortality ratio (MMR) is part of goal 3 in the global sustainable development goals (SDGs), and previously, it was an important ...

FertilitY Predictor-a machine learning-based web tool for the prediction of assisted reproduction outcomes in men with Y chromosome microdeletions.

Journal of assisted reproduction and genetics
PURPOSE: Y chromosome microdeletions (YCMD) are a common cause of azoospermia and oligozoospermia in men. Herein, we developed a machine learning-based web tool to predict sperm retrieval rates and success rates of assisted reproduction (ART) in men ...