AI Medical Compendium Journal:
Journal of assisted reproduction and genetics

Showing 11 to 20 of 42 articles

Comparing performance between clinics of an embryo evaluation algorithm based on time-lapse images and machine learning.

Journal of assisted reproduction and genetics
PURPOSE: This article aims to assess how differences in maternal age distributions between IVF clinics affect the performance of an artificial intelligence model for embryo viability prediction and proposes a method to account for such differences.

Detection of spermatogonial stem/progenitor cells in prepubertal mouse testis with deep learning.

Journal of assisted reproduction and genetics
PURPOSE: Rapid and easy detection of spermatogonial stem/progenitor cells (SSPCs) is crucial for clinicians dealing with male infertility caused by prepubertal testicular damage. Deep learning (DL) methods may offer visual tools for tracking SSPCs on...

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...

New frontiers in embryo selection.

Journal of assisted reproduction and genetics
Human infertility is a major global public health issue estimated to affect one out of six couples, while the number of assisted reproduction cycles grows impressively year over year. Efforts to alleviate infertility using advanced technology are gai...

Advancements in the future of automating micromanipulation techniques in the IVF laboratory using deep convolutional neural networks.

Journal of assisted reproduction and genetics
PURPOSE: To determine if deep learning artificial intelligence algorithms can be used to accurately identify key morphologic landmarks on oocytes and cleavage stage embryo images for micromanipulation procedures such as intracytoplasmic sperm injecti...

Looking with new eyes: advanced microscopy and artificial intelligence in reproductive medicine.

Journal of assisted reproduction and genetics
Microscopy has long played a pivotal role in the field of assisted reproductive technology (ART). The advent of artificial intelligence (AI) has opened the door for new approaches to sperm and oocyte assessment and selection, with the potential for i...

Quality assurance (QA) for monitoring the performance of assisted reproductive technology (ART) staff using artificial intelligence (AI).

Journal of assisted reproduction and genetics
PURPOSE: Deep learning neural networks have been used to predict the developmental fate and implantation potential of embryos with high accuracy. Such networks have been used as an assistive quality assurance (QA) tool to identify perturbations in th...

Using artificial intelligence to avoid human error in identifying embryos: a retrospective cohort study.

Journal of assisted reproduction and genetics
PURPOSE: To determine whether convolutional neural networks (CNN) can be used to accurately ascertain the patient identity (ID) of cleavage and blastocyst stage embryos based on image data alone.