AIMC Topic: Pregnancy
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Automated approach for fetal and maternal health management using light gradient boosting model with SHAP explainable AI.
Frontiers in public health
Dec 20, 2024
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...
Enhancing decision-making in tubal ectopic pregnancy using a machine learning approach to expectant management: a clinical article.
BMC pregnancy and childbirth
Dec 19, 2024
OBJECTIVE: To refine decision-making regarding expectant management for ectopic pregnancy (EP) using machine learning.
Cost-effectiveness analysis of AI-based image quality control for perinatal ultrasound screening.
BMC medical education
Dec 18, 2024
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
Dec 18, 2024
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
Dec 18, 2024
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
Dec 18, 2024
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
Dec 9, 2024
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 ...
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 ...
Prediction of preterm birth using machine learning: a comprehensive analysis based on large-scale preschool children survey data in Shenzhen of China.
BMC pregnancy and childbirth
Dec 4, 2024
BACKGROUND: Preterm birth (PTB) is a significant cause of neonatal mortality and long-term health issues. Accurate prediction and timely prevention of PTB are essential for reducing associated child mortality and morbidity. Traditional predictive met...
Predictive efficacy of machine-learning algorithms on intrahepatic cholestasis of pregnancy based on clinical and laboratory indicators.
The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians
Dec 3, 2024
OBJECTIVES: Intrahepatic cholestasis of pregnancy (ICP), a condition exclusive to pregnancy, necessitates prompt identification and intervention to improve the perinatal outcomes. This study aims to develop suitable machine-learning models for predic...
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