AIMC Topic: Oocytes
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An artificial intelligence platform to optimize workflow during ovarian stimulation and IVF: process improvement and outcome-based predictions.
Reproductive biomedicine online
Oct 20, 2021
RESEARCH QUESTION: Can workflow during IVF be facilitated by artificial intelligence to limit monitoring during ovarian stimulation to a single day and enable level-loading of retrievals?
Semantic segmentation of human oocyte images using deep neural networks.
Biomedical engineering online
Apr 23, 2021
BACKGROUND: Infertility is a significant problem of humanity. In vitro fertilisation is one of the most effective and frequently applied ART methods. The effectiveness IVF depends on the assessment and selection of gametes and embryo with the highest...
Three ways of knowing: the integration of clinical expertise, evidence-based medicine, and artificial intelligence in assisted reproductive technologies.
Journal of assisted reproduction and genetics
Apr 19, 2021
Decision-making in fertility care is on the cusp of a significant frameshift. Online tools to integrate artificial intelligence into the decision-making process across all aspects of ART are rapidly emerging. These tools have the potential to improve...
A robust deep learning-based multiclass segmentation method for analyzing human metaphase II oocyte images.
Computer methods and programs in biomedicine
Jan 19, 2021
BACKGROUND AND OBJECTIVE: The morphology of the human metaphase II (MII) oocyte is an essential indicator of the embryo's potential for developing into a healthy baby in the Intra-Cytoplasmic Sperm Injection (ICSI) process. In this case, characterist...
Machine learning vs. classic statistics for the prediction of IVF outcomes.
Journal of assisted reproduction and genetics
Aug 11, 2020
PURPOSE: To assess whether machine learning methods provide advantage over classic statistical modeling for the prediction of IVF outcomes.
Predicting pregnancy test results after embryo transfer by image feature extraction and analysis using machine learning.
Scientific reports
Mar 10, 2020
Assessing the viability of a blastosyst is still empirical and non-reproducible nowadays. We developed an algorithm based on artificial vision and machine learning (and other classifiers) that predicts pregnancy using the beta human chorionic gonadot...
Visual Servoed Robotic Mouse Oocyte Rotation.
IEEE transactions on bio-medical engineering
Dec 23, 2019
UNLABELLED: Both injection and biopsy of a mammalian cell require positioning and orientation of a biological cell in a three-dimensional space under a microscope. Manual cell manipulation and orientation is the most commonly used method that is base...
Democratized image analytics by visual programming through integration of deep models and small-scale machine learning.
Nature communications
Oct 7, 2019
Analysis of biomedical images requires computational expertize that are uncommon among biomedical scientists. Deep learning approaches for image analysis provide an opportunity to develop user-friendly tools for exploratory data analysis. Here, we us...
Artificial intelligence and machine learning for human reproduction and embryology presented at ASRM and ESHRE 2018.
Journal of assisted reproduction and genetics
Jan 28, 2019
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...
In vitro survival, growth, and maturation of sheep oocytes from secondary follicles cultured in serum-free conditions: impact of a constant or a sequential medium containing recombinant human FSH.
Domestic animal endocrinology
Dec 18, 2018
This study evaluated the in vitro development and maturation of ovine oocytes from secondary follicles cultured in serum-free medium containing fixed or sequential concentrations of recombinant human FSH (rhFSH). Follicles were cultured in α-MEM alon...
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