AIMC Topic: Pregnancy
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Integrating SHAP analysis with machine learning to predict postpartum hemorrhage in vaginal births.
BMC pregnancy and childbirth
May 3, 2025
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...
Predicting preeclampsia in early pregnancy using clinical and laboratory data via machine learning model.
BMC medical informatics and decision making
May 1, 2025
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...
Investigating Protective and Risk Factors and Predictive Insights for Aboriginal Perinatal Mental Health: Explainable Artificial Intelligence Approach.
Journal of medical Internet research
Apr 30, 2025
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 ...
[Artificial intelligence and ultrasound in fetal medicine].
Ugeskrift for laeger
Apr 28, 2025
Ultrasound is essential in fetal medicine for diagnosing and monitoring, but it requires extensive training. Artificial intelligence (AI) shows a great promise in enhancing the clinical training and practice, by improving workflow and standardising d...
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
Apr 27, 2025
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...
Performance of ChatGPT and Microsoft Copilot in Bing in answering obstetric ultrasound questions and analyzing obstetric ultrasound reports.
Scientific reports
Apr 26, 2025
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...
Deep learning for fetal inflammatory response diagnosis in the umbilical cord.
Placenta
Apr 24, 2025
INTRODUCTION: Inflammation of the umbilical cord can be seen as a result of ascending intrauterine infection or other inflammatory stimuli. Acute fetal inflammatory response (FIR) is characterized by infiltration of the umbilical cord by fetal neutro...
Effect of pregnancy and infancy exposure to outdoor particulate matter (PM, PM, PM) and SO on childhood pneumonia in preschool children in Taiyuan City, China.
Environmental pollution (Barking, Essex : 1987)
Apr 24, 2025
There is currently a paucity of research on the effects of early life exposure to particulate matter (PM) of various size fractions on pneumonia in preschool-aged children. We explored the connections between antenatal and postnatal exposure to atmos...
Birth weight prediction using artificial intelligence-based placental assessment from macroscopic photo: a retrospective study.
Placenta
Apr 23, 2025
BACKGROUND: This study aimed to predict newborn birth weight through multifactorial analysis of macroscopic placental images using artificial intelligence (AI).
GDM-BC: Non-invasive body composition dataset for intelligent prediction of Gestational Diabetes Mellitus.
Computers in biology and medicine
Apr 23, 2025
Gestational Diabetes Mellitus (GDM) refers to any degree of impaired glucose tolerance with onset or first recognition during pregnancy. As a high-prevalence disease, GDM damages the health of both pregnant women and fetuses in the short and long ter...
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