AIMC Topic: Pregnancy

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Harnessing vaginal inflammation and microbiome: a machine learning model for predicting IVF success.

NPJ biofilms and microbiomes
Humans are the only species with a commensal Lactobacillus-dominant vaginal microbiota. Reproductive tract microbes have been linked to fertility outcomes, as has intrauterine inflammation, suggesting immune response may mediate adverse outcomes. In ...

Advancing prenatal healthcare by explainable AI enhanced fetal ultrasound image segmentation using U-Net++ with attention mechanisms.

Scientific reports
Prenatal healthcare development requires accurate automated techniques for fetal ultrasound image segmentation. This approach allows standardized evaluation of fetal development by minimizing time-exhaustive processes that perform poorly due to human...

Automated interpretation of cardiotocography using deep learning in a nationwide multicenter study.

Scientific reports
Timely detection of abnormal cardiotocography (CTG) during labor plays a crucial role in enhancing fetal prognosis. Recent research has explored the use of deep learning for CTG interpretation, most studies rely on small, localized datasets or focus ...

Determining the risk of gestational diabetes using machine learning: A study on first-trimester PAPP-A and β-hCG data.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: To evaluate the predictive potential of first-trimester biomarkers-pregnancy-associated plasma protein-A (PAPP-A) and free β-human chorionic gonadotropin (β-hCG)-combined with maternal body mass index (BMI), using machine learning (ML) alg...

Artificial intelligence in prediction of postpartum hemorrhage: a primer and review.

International journal of obstetric anesthesia
Postpartum hemorrhage (PPH) is a leading cause of maternal mortality worldwide, and the ability to predict PPH may help address preventable causes of morbidity and mortality such as delays in care. Understanding the importance of standardized approac...

The Effect of a Generative AI-Based Teaching Strategy on Building Students' Competency.

The Journal of nursing education
BACKGROUND: Assessment of the initial medical history data for pregnant women is an essential component of nursing training. Therefore, understanding clinical patient characteristics is crucial for developing students' ability to independently manage...

TRAF3 as a potential diagnostic biomarker for recurrent pregnancy loss: insights from single-cell transcriptomics and machine learning.

BMC pregnancy and childbirth
BACKGROUND: Recurrent pregnancy loss (RPL), characterized by multiple miscarriages, remains a condition with unclear etiology, posing significant challenges for affected women and couples. This study aims to explore the underlying mechanisms of RPL, ...

Undesired nexus poor health status of child under-five: A case study of Pakistan.

PloS one
Childhood morbidity and mortality are key indicators of human development, particularly reflecting poor health conditions in children. In Pakistan, child mortality remains a serious problem despite efforts to reduce it. One factor that may be associa...

OSAM-NET: A multi-feature fusion model for measuring fetal head flexion during labor with transformer multi-head self-attention.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Fetal head flexion is essential during labor. The current assessment presents technical challenges for unskilled ultrasound operators. Therefore, the study aimed to propose an occiput-spine angle measurement network (OSAM-NET) to improve the accuracy...