AI Medical Compendium Topic

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Endometrium

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Multifactor Prediction of Embryo Transfer Outcomes Based on a Machine Learning Algorithm.

Frontiers in endocrinology
fertilization-embryo transfer (IVF-ET) technology make it possible for infertile couples to conceive a baby successfully. Nevertheless, IVF-ET does not guarantee success. Frozen embryo transfer (FET) is an important supplement to IVF-ET. Many factor...

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
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...

Performance of automatic machine learning versus radiologists in the evaluation of endometrium on computed tomography.

Abdominal radiology (New York)
PURPOSE: In this study, we developed radiomic models that utilize a combination of imaging features and clinical variables to distinguish endometrial cancer (EC) from normal endometrium on routine computed tomography (CT).

Artificial Intelligence in the Assessment of Female Reproductive Function Using Ultrasound: A Review.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
The incidence of infertility is continuously increasing nearly all over the world in recent years, and novel methods for accurate assessment are of great need. Artificial Intelligence (AI) has gradually become an effective supplementary method for th...

HOX cluster and their cofactors showed an altered expression pattern in eutopic and ectopic endometriosis tissues.

Reproductive biology and endocrinology : RB&E
Endometriosis is major gynecological disease that affects over 10% of women worldwide and 30%-50% of these women have pelvic pain, abnormal uterine bleeding and infertility. The cause of endometriosis is unknown and there is no definite cure mainly b...

Artificial intelligence deep learning model assessment of leukocyte counts and proliferation in endometrium from women with and without polycystic ovary syndrome.

F&S science
OBJECTIVE: To study whether artificial intelligence (AI) technology can be used to discern quantitative differences in endometrial immune cells between cycle phases and between samples from women with polycystic ovary syndrome (PCOS) and non-PCOS con...

Validation of a deep learning-based image analysis system to diagnose subclinical endometritis in dairy cows.

PloS one
The assessment of polymorphonuclear leukocyte (PMN) proportions (%) of endometrial samples is the hallmark for subclinical endometritis (SCE) diagnosis. Yet, a non-biased, automated diagnostic method for assessing PMN% in endometrial cytology slides ...

Deep learning analysis of endometrial histology as a promising tool to predict the chance of pregnancy after frozen embryo transfers.

Journal of assisted reproduction and genetics
PURPOSE: Endometrial histology on hematoxylin and eosin (H&E)-stained preparations provides information associated with receptivity. However, traditional histological examination by Noyes' dating method is of limited value as it is prone to subjectiv...

Machine learning to identify endometrial biomarkers predictive of pregnancy success following artificial insemination in dairy cows†.

Biology of reproduction
The objective was to identify a set of genes whose transcript abundance is predictive of a cow's ability to become pregnant following artificial insemination. Endometrial epithelial cells from the uterine body were collected for RNA sequencing using ...