AI Medical Compendium Topic:
Pregnancy

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Integrated Learning: Screening Optimal Biomarkers for Identifying Preeclampsia in Placental mRNA Samples.

Computational and mathematical methods in medicine
Preeclampsia (PE) is a maternal disease that causes maternal and child death. Treatment and preventive measures are not sound enough. The problem of PE screening has attracted much attention. The purpose of this study is to screen placental mRNA to o...

Intrahepatic cholestasis of pregnancy: machine-learning algorithm to predict elevated bile acid based on clinical and laboratory data.

Archives of gynecology and obstetrics
PURPOSE: Applying machine-learning models to clinical and laboratory features of women with intrahepatic cholestasis of pregnancy (ICP) and creating algorithm to identify these patients without bile acid measurements.

Recognition of facial expression of fetuses by artificial intelligence (AI).

Journal of perinatal medicine
OBJECTIVES: The development of the artificial intelligence (AI) classifier to recognize fetal facial expressions that are considered as being related to the brain development of fetuses as a retrospective, non-interventional pilot study.

Integrated analysis of multiple microarray studies to identify novel gene signatures in preeclampsia.

Placenta
INTRODUCTION: Preeclampsia (PE) is one of the major causes of maternal and fetal morbidity and mortality in pregnancy worldwide. However, the intrinsic molecular mechanisms underlying the pathogenesis of PE have not yet been fully elucidated.

Mutual Information-Based Disentangled Neural Networks for Classifying Unseen Categories in Different Domains: Application to Fetal Ultrasound Imaging.

IEEE transactions on medical imaging
Deep neural networks exhibit limited generalizability across images with different entangled domain features and categorical features. Learning generalizable features that can form universal categorical decision boundaries across domains is an intere...

Fetal birthweight prediction with measured data by a temporal machine learning method.

BMC medical informatics and decision making
BACKGROUND: Birthweight is an important indicator during the fetal development process to protect the maternal and infant safety. However, birthweight is difficult to be directly measured, and is usually roughly estimated by the empirical formulas ac...

Application of convolutional neural network on early human embryo segmentation during in vitro fertilization.

Journal of cellular and molecular medicine
Selection of the best quality embryo is the key for a faithful implantation in in vitro fertilization (IVF) practice. However, the process of evaluating numerous images captured by time-lapse imaging (TLI) system is time-consuming and some important ...

Knowledge representation and learning of operator clinical workflow from full-length routine fetal ultrasound scan videos.

Medical image analysis
Ultrasound is a widely used imaging modality, yet it is well-known that scanning can be highly operator-dependent and difficult to perform, which limits its wider use in clinical practice. The literature on understanding what makes clinical sonograph...

Predicting pregnancy status from mid-infrared spectroscopy in dairy cow milk using deep learning.

Journal of dairy science
Accurately identifying pregnancy status is imperative for a profitable dairy enterprise. Mid-infrared (MIR) spectroscopy is routinely used to determine fat and protein concentrations in milk samples. Mid-infrared spectra have successfully been used t...