AIMC Topic: Pregnancy

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Real-Time Identification of Cricothyrotomy Landmarks in Emergency Care and Obstetric Patients Using Wireless Handheld Ultrasound and Edge-Computing Artificial Intelligence: A Prospective Observational Study.

Journal of medical systems
This study aimed to develop machine learning-based algorithms to assist physicians in ultrasound-guided localization of the cricoid cartilage (CC), thyroid cartilage (TC), and cricothyroid membrane (CTM) for cricothyroidotomy. Adult female participan...

Application of machine learning to predict delayed fecundability among women in sub-Saharan Africa.

Reproduction & fertility
ABSTRACT: Delayed fecundability, defined as trying to conceive for ≥12 months without success, is a growing global concern due to the threat of fertility rates falling below the replacement level. This study aimed to predict delayed fecundability and...

Leveraging machine learning to predict mosquito bed net utilization among women of reproductive age in sub-Saharan Africa.

Malaria journal
BACKGROUND: Malaria remains a major public health challenge, particularly in sub-Saharan Africa, where women of reproductive age are especially vulnerable during pregnancy and childbirth. To identify key predictors and improve predictive accuracy, ma...

Comprehensive identification of immune-related biomarkers and therapeutic targets in preeclampsia: integrative bioinformatics and experimental validation.

BMC pregnancy and childbirth
BACKGROUND: Preeclampsia (PE) is a serious hypertensive complication during pregnancy characterized by immune dysregulation and vascular dysfunction, however, the precise molecular mechanisms and effective therapeutic strategies remain unclear. This ...

Identifying prenatal risk factors of postpartum depression with machine learning.

Scientific reports
Postpartum depression (PPD), a common mental illness among mothers, can affect the well-being of both mothers and their children. Early intervention is essential but hindered by difficulties in identifying at-risk women, as it remains unclear how soo...

Hybrid-MedNet: a hybrid CNN-transformer network with multi-dimensional feature fusion for medical image segmentation.

Physics in medicine and biology
Twin-to-twin transfusion syndrome (TTTS) is a complex prenatal condition in which monochorionic twins experience an imbalance in blood flow due to abnormal vascular connections in the shared placenta. Fetoscopic laser photocoagulation is the first-li...

FetalDenseNet: multi-scale deep learning for enhanced early detection of fetal anatomical planes in prenatal ultrasound.

Journal of perinatal medicine
OBJECTIVES: The study aims to improve the classification of fetal anatomical planes using Deep Learning (DL) methods to enhance the accuracy of fetal ultrasound interpretation.

Predictive models for live birth outcomes following fresh embryo transfer in assisted reproductive technologies using machine learning.

Journal of translational medicine
BACKGROUND: Infertility affects approximately 15% of couples globally, with assisted reproductive technologies (ARTs) becoming the primary interventions. Despite the growing use of ARTs, success rates have plateaued at around 30%, highlighting the ne...

Interpretable Machine Learning for Predicting Adverse Pregnancy Outcomes in Gestational Diabetes: Retrospective Cohort Study.

JMIR medical informatics
BACKGROUND: Gestational diabetes mellitus (GDM) affects over 5% of pregnancies worldwide, elevating risks of type 2 diabetes post partum and complications such as fetal death, miscarriage, and congenital abnormalities. Effective GDM management is ess...

Advantages of fully automated AI-enhanced algorithm (5D CNS+™) for generating a fetal neurosonogram in clinical routine.

Journal of perinatal medicine
OBJECTIVES: The objective was to demonstrate superiority of a fully vs. semi-automated approach (5D CNS+™) and to verify operators could handle and benefit from a fully automated rendering volumetric datasets to generate a complete fetal neurosonogra...