AI Medical Compendium Topic:
Pregnancy

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Exon level machine learning analyses elucidate novel candidate miRNA targets in an avian model of fetal alcohol spectrum disorder.

PLoS computational biology
Gestational alcohol exposure causes fetal alcohol spectrum disorder (FASD) and is a prominent cause of neurodevelopmental disability. Whole transcriptome sequencing (RNA-Seq) offer insights into mechanisms underlying FASD, but gene-level analysis pro...

Prediction of fetal state from the cardiotocogram recordings using neural network models.

Artificial intelligence in medicine
The combination of machine vision and soft computing approaches in the clinical decisions, using training data, can improve medical decisions and treatments. The cardiotocography (CTG) monitoring and uterine activity (UA) provides useful information ...

Decision Fusion-Based Fetal Ultrasound Image Plane Classification Using Convolutional Neural Networks.

Ultrasound in medicine & biology
Machine learning for ultrasound image analysis and interpretation can be helpful in automated image classification in large-scale retrospective analyses to objectively derive new indicators of abnormal fetal development that are embedded in ultrasoun...

Evaluating reinforcement learning agents for anatomical landmark detection.

Medical image analysis
Automatic detection of anatomical landmarks is an important step for a wide range of applications in medical image analysis. Manual annotation of landmarks is a tedious task and prone to observer errors. In this paper, we evaluate novel deep reinforc...

Attention gated networks: Learning to leverage salient regions in medical images.

Medical image analysis
We propose a novel attention gate (AG) model for medical image analysis that automatically learns to focus on target structures of varying shapes and sizes. Models trained with AGs implicitly learn to suppress irrelevant regions in an input image whi...

Artificial intelligence and machine learning for human reproduction and embryology presented at ASRM and ESHRE 2018.

Journal of assisted reproduction and genetics
Sixteen artificial intelligence (AI) and machine learning (ML) approaches were reported at the 2018 annual congresses of the American Society for Reproductive Biology (9) and European Society for Human Reproduction and Embryology (7). Nearly every as...

Prediction of implantation after blastocyst transfer in in vitro fertilization: a machine-learning perspective.

Fertility and sterility
OBJECTIVE: To develop a random forest model (RFM) to predict implantation potential of a transferred embryo and compare it with a multivariate logistic regression model (MvLRM), based on data from a large cohort including in vitro fertilization (IVF)...

Association between prenatal exposure to multiple persistent organic pollutants (POPs) and growth indicators in newborns.

Environmental research
Despite the fact that many of persistent organic pollutants (POPs) have been banned for decades, they still constitute a group of harmful substances to human health. Prenatal exposure can have adverse effects on one's health as well as on their newbo...

Effect of dietary n-3 polyunsaturated fatty acid supplementation and post-insemination plane of nutrition on systemic concentrations of metabolic analytes, progesterone, hepatic gene expression and embryo development and survival in beef heifers.

Theriogenology
Nutrition, and particularly dietary energy intake, plays a fundamental role in reproductive function in cattle. There is some evidence that supplemental omega-3 dietary polyunsaturated fatty acids (n-3 PUFA) can exert positive effects on fertility. T...

A machine learning approach to investigate potential risk factors for gastroschisis in California.

Birth defects research
BACKGROUND: To generate new leads about risk factors for gastroschisis, a birth defect that has been increasing in prevalence over time, we performed an untargeted data mining statistical approach.