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Pregnancy

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Performance of ChatGPT and Microsoft Copilot in Bing in answering obstetric ultrasound questions and analyzing obstetric ultrasound reports.

Scientific reports
To evaluate and compare the performance of publicly available ChatGPT-3.5, ChatGPT-4.0 and Microsoft Copilot in Bing (Copilot) in answering obstetric ultrasound questions and analyzing obstetric ultrasound reports. Twenty questions related to obstetr...

Optimizing predictive features using machine learning for early miscarriage risk following single vitrified-warmed blastocyst transfer.

Frontiers in endocrinology
RESEARCH QUESTION: Can machine learning models accurately predict the risk of early miscarriage following single vitrified-warmed blastocyst transfer (SVBT)?

Predicting Risk for Patent Ductus Arteriosus in the Neonate: A Machine Learning Analysis.

Medicina (Kaunas, Lithuania)
: Patent ductus arteriosus (PDA) is common in newborns, being associated with high morbidity and mortality. While maternal and neonatal conditions are known contributors, few studies use advanced machine learning (ML) as predictive factors. This stud...

The Artificial Intelligence-Enhanced Echocardiographic Detection of Congenital Heart Defects in the Fetus: A Mini-Review.

Medicina (Kaunas, Lithuania)
Artificial intelligence (AI) is rapidly gaining attention in radiology and cardiology for accurately diagnosing structural heart disease. In this review paper, we first outline the technical background of AI and echocardiography and then present an a...

Investigating Protective and Risk Factors and Predictive Insights for Aboriginal Perinatal Mental Health: Explainable Artificial Intelligence Approach.

Journal of medical Internet research
BACKGROUND: Perinatal depression and anxiety significantly impact maternal and infant health, potentially leading to severe outcomes like preterm birth and suicide. Aboriginal women, despite their resilience, face elevated risks due to the long-term ...

The role of artificial intelligence in the prediction, identification, diagnosis and treatment of perinatal depression and anxiety among women in LMICs: a systematic review protocol.

BMJ open
INTRODUCTION: Perinatal depression and anxiety (PDA) is associated with a high risk of maternal mortality. Existing data shows that 95% of maternal mortality in low- and middle-income countries (LMICs) is due to resource constraints and negligence in...

Random forest algorithm for predicting tobacco use and identifying determinants among pregnant women in 26 sub-Saharan African countries: a 2024 analysis.

BMC public health
INTRODUCTION: Tobacco use during pregnancy is a significant public health concern, associated with adverse maternal and neonatal outcomes. Despite its critical importance, comprehensive data on tobacco use among pregnant women in sub-Saharan Africa i...

Integrating SHAP analysis with machine learning to predict postpartum hemorrhage in vaginal births.

BMC pregnancy and childbirth
OBJECTIVE: This study aimed to develop a machine learning (ML) model integrated with SHapley Additive exPlanations (SHAP) analysis to predict postpartum hemorrhage (PPH) following vaginal deliveries, offering a potential tool for personalized risk as...

Prediction of high-risk pregnancy based on machine learning algorithms.

Scientific reports
This study explores the application of machine learning algorithms in predicting high-risk pregnancy among expectant mothers, aiming to construct an efficient predictive model to improve maternal health management. The study is based on the maternal ...

Predicting preeclampsia in early pregnancy using clinical and laboratory data via machine learning model.

BMC medical informatics and decision making
BACKGROUND: This study was performed to characterize the relationship of various laboratory test indicators with clinical information and Preeclampsia (PE) development. Then, prediction models for early-onset preeclampsia (EOPE), late-onset preeclamp...