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Pregnancy

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Application of machine learning methods for predicting under-five mortality: analysis of Nigerian demographic health survey 2018 dataset.

BMC medical informatics and decision making
BACKGROUND: Under-five mortality remains a significant public health issue in developing countries. This study aimed to assess the effectiveness of various machine learning algorithms in predicting under-five mortality in Nigeria and identify the mos...

Artificial Intelligence in Imaging in the First Trimester of Pregnancy: A Systematic Review.

Fetal diagnosis and therapy
INTRODUCTION: Ultrasonography in the first trimester of pregnancy offers an early screening tool to identify high risk pregnancies. Artificial intelligence (AI) algorithms have the potential to improve the accuracy of diagnosis and assist the clinici...

Predictive value of ultrasonic artificial intelligence in placental characteristics of early pregnancy for gestational diabetes mellitus.

Frontiers in endocrinology
BACKGROUND: To explore the predictive value of placental features in early pregnancy for gestational diabetes mellitus (GDM) using deep and radiomics-based machine learning (ML) applied to ultrasound imaging (USI), and to develop a nomogram in conjun...

Application of artificial neural networks to evaluate femur development in the human fetus.

PloS one
The present article concentrates on an innovative analysis that was performed to assess the development of the femur in human fetuses using artificial intelligence. As a prerequisite, linear dimensions, cross-sectional surface areas and volumes of th...

Enhancing gestational diabetes mellitus risk assessment and treatment through GDMPredictor: a machine learning approach.

Journal of endocrinological investigation
BACKGROUND: Gestational diabetes mellitus (GDM) is a serious health concern that affects pregnant women worldwide and can lead to adverse pregnancy outcomes. Early detection of high-risk individuals and the implementation of appropriate treatment can...

Computational Approaches for Predicting Preterm Birth and Newborn Outcomes.

Clinics in perinatology
Preterm birth (PTB) and its associated morbidities are a leading cause of infant mortality and morbidity. Accurate predictive models and a better biological understanding of PTB-associated morbidities are critical in reducing their adverse effects. I...

Research on Human-Robot Collaboration Method for Parallel Robots Oriented to Segment Docking.

Sensors (Basel, Switzerland)
In the field of aerospace, large and heavy cabin segments present a significant challenge in assembling space engines. The substantial inertial force of cabin segments' mass often leads to unexpected motion during docking, resulting in segment collis...

Assessment of artificial intelligence model and manual morphokinetic annotation system as embryo grading methods for successful live birth prediction: a retrospective monocentric study.

Reproductive biology and endocrinology : RB&E
PURPOSE: The introduction of the time-lapse monitoring system (TMS) and the development of predictive algorithms could contribute to the optimal embryos selection for transfer. Therefore, the present study aims at investigating the efficiency of KIDS...

Development and validation of an electrocardiographic artificial intelligence model for detection of peripartum cardiomyopathy.

American journal of obstetrics & gynecology MFM
BACKGROUND: This study used electrocardiogram data in conjunction with artificial intelligence methods as a noninvasive tool for detecting peripartum cardiomyopathy.