AIMC Topic: Pregnancy
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Deep learning model for predicting gestational age after the first trimester using fetal MRI.
European radiology
Apr 14, 2021
OBJECTIVES: To evaluate a deep learning model for predicting gestational age from fetal brain MRI acquired after the first trimester in comparison to biparietal diameter (BPD).
A prediction model using machine-learning algorithm for assessing intrathecal hyperbaric bupivacaine dose during cesarean section.
BMC anesthesiology
Apr 14, 2021
BACKGROUND: The intrathecal hyperbaric bupivacaine dosage for cesarean section is difficult to predetermine. This study aimed to develop a decision-support model using a machine-learning algorithm for assessing intrathecal hyperbaric bupivacaine dose...
Prediction of Streptococcus uberis clinical mastitis treatment success in dairy herds by means of mass spectrometry and machine-learning.
Scientific reports
Apr 8, 2021
Streptococcus uberis is one of the leading pathogens causing mastitis worldwide. Identification of S. uberis strains that fail to respond to treatment with antibiotics is essential for better decision making and treatment selection. We demonstrate th...
Individualized embryo selection strategy developed by stacking machine learning model for better in vitro fertilization outcomes: an application study.
Reproductive biology and endocrinology : RB&E
Apr 5, 2021
BACKGROUND: To minimize the rate of in vitro fertilization (IVF)- associated multiple-embryo gestation, significant efforts have been made. Previous studies related to machine learning in IVF mainly focused on selecting the top-quality embryos to imp...
Review of computer vision application in in vitro fertilization: the application of deep learning-based computer vision technology in the world of IVF.
Journal of assisted reproduction and genetics
Apr 3, 2021
In vitro fertilization has been regarded as a forefront solution in treating infertility for over four decades, yet its effectiveness has remained relatively low. This could be attributed to the lack of advancements for the method of observing and se...
Using Deep Learning in a Monocentric Study to Characterize Maternal Immune Environment for Predicting Pregnancy Outcomes in the Recurrent Reproductive Failure Patients.
Frontiers in immunology
Apr 1, 2021
Recurrent reproductive failure (RRF), such as recurrent pregnancy loss and repeated implantation failure, is characterized by complex etiologies and particularly associated with diverse maternal factors. It is currently believed that RRF is closely a...
Machine learning analysis of pregnancy data enables early identification of a subpopulation of newborns with ASD.
Scientific reports
Mar 25, 2021
To identify newborns at risk of developing ASD and to detect ASD biomarkers early after birth, we compared retrospectively ultrasound and biological measurements of babies diagnosed later with ASD or neurotypical (NT) that are collected routinely dur...
Proposing a machine-learning based method to predict stillbirth before and during delivery and ranking the features: nationwide retrospective cross-sectional study.
BMC pregnancy and childbirth
Mar 12, 2021
BACKGROUND: Stillbirth is defined as fetal loss in pregnancy beyond 28 weeks by WHO. In this study, a machine-learning based method is proposed to predict stillbirth from livebirth and discriminate stillbirth before and during delivery and rank the f...
Detection of prenatal alcohol exposure using machine learning classification of resting-state functional network connectivity data.
Alcohol (Fayetteville, N.Y.)
Mar 11, 2021
Fetal Alcohol Spectrum Disorder (FASD), a wide range of physical and neurobehavioral abnormalities associated with prenatal alcohol exposure (PAE), is recognized as a significant public health concern. Advancements in the diagnosis of FASD have been ...
Deep learning neural network analysis of human blastocyst expansion from time-lapse image files.
Reproductive biomedicine online
Mar 6, 2021
RESEARCH QUESTION: Can artificial intelligence (AI) discriminate a blastocyst's cellular area from unedited time-lapse image files using semantic segmentation and a deep learning optimized U-Net architecture for use in selecting single blastocysts fo...
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