AIMC Topic: Embryo, Mammalian

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Machine learning-assisted high-content analysis of pluripotent stem cell-derived embryos in vitro.

Stem cell reports Apr 22, 2021
Stem cell-based embryo models by cultured pluripotent and extra-embryonic lineage stem cells are novel platforms to model early postimplantation development. We showed that induced pluripotent stem cells (iPSCs) could form ITS (iPSCs and trophectoder...
Endoderm Bone Morphogenetic Protein 4 Small Molecule Libraries Trophoblasts Gene Expression Regulation, Developmental Induced Pluripotent Stem Cells Morphogenesis Cell Polarity Ectoderm Transcriptome Mice Embryo Implantation Embryo, Mammalian Machine Learning Cytokines Animals
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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...
Computer Simulation Prognosis Pregnancy Female Humans Artificial Intelligence Treatment Outcome Adult Machine Learning Embryo, Mammalian Models, Statistical Male Pregnancy Rate Infertility Fertilization in Vitro Single Embryo Transfer
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Fast and precise single-cell data analysis using a hierarchical autoencoder.

Nature communications Feb 15, 2021
A primary challenge in single-cell RNA sequencing (scRNA-seq) studies comes from the massive amount of data and the excess noise level. To address this challenge, we introduce an analysis framework, named single-cell Decomposition using Hierarchical ...
Sequence Analysis, RNA Liver Unsupervised Machine Learning Bayes Theorem Animals Lung Single-Cell Analysis Mice Pancreas Zygote Cell Separation Mouse Embryonic Stem Cells Benchmarking Retina Cerebellum Embryo, Mammalian Humans Neural Networks, Computer Visual Cortex
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Application of convolutional neural network on early human embryo segmentation during in vitro fertilization.

Journal of cellular and molecular medicine Jan 24, 2021
Selection of the best quality embryo is the key for a faithful implantation in in vitro fertilization (IVF) practice. However, the process of evaluating numerous images captured by time-lapse imaging (TLI) system is time-consuming and some important ...
Embryo, Mammalian Embryonic Development Cell Culture Techniques Time-Lapse Imaging Humans Neural Networks, Computer Female Cells, Cultured Fertilization in Vitro Pregnancy Models, Biological
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Towards the selection of embryos with the greatest implantation potential.

Journal of obstetrics and gynaecology : the journal of the Institute of Obstetrics and Gynaecology Jan 12, 2021
Choosing the most suitable embryo remains challenging as the standard approach to select top-quality embryos for transfer rely on static morphological assessment. It is completed after fertilisation, on days 3 and 5 post oocyte retrieval and evaluate...
Fertilization in Vitro Genetic Testing Aneuploidy Embryo, Mammalian Embryonic Development Chromosome Aberrations Humans Artificial Intelligence Pregnancy Female
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Choosing the best embryo with the help of artificial intelligence.

Fertility and sterility Nov 1, 2020
Embryo Implantation Humans Embryo, Mammalian Neural Networks, Computer Artificial Intelligence
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3D convolutional neural networks-based segmentation to acquire quantitative criteria of the nucleus during mouse embryogenesis.

NPJ systems biology and applications Oct 20, 2020
During embryogenesis, cells repeatedly divide and dynamically change their positions in three-dimensional (3D) space. A robust and accurate algorithm to acquire the 3D positions of the cells would help to reveal the mechanisms of embryogenesis. To ac...
Neural Networks, Computer Animals Imaging, Three-Dimensional Cell Nucleus Mice Microscopy, Fluorescence Embryo, Mammalian Embryonic Development
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CytoCensus, mapping cell identity and division in tissues and organs using machine learning.

eLife May 19, 2020
A major challenge in cell and developmental biology is the automated identification and quantitation of cells in complex multilayered tissues. We developed CytoCensus: an easily deployed implementation of supervised machine learning that extends conv...
Cell Division Tissue Culture Techniques Time-Lapse Imaging Microscopy, Video Organoids Embryo, Mammalian Animals, Genetically Modified Automation Drosophila melanogaster Mice Mutation Machine Learning Retina Male Phenotype Zebrafish Larva Time Factors Brain Image Processing, Computer-Assisted Female Reproducibility of Results Animals
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Investigating the gene expression profiles of cells in seven embryonic stages with machine learning algorithms.

Genomics Feb 8, 2020
The development of embryonic cells involves several continuous stages, and some genes are related to embryogenesis. To date, few studies have systematically investigated changes in gene expression profiles during mammalian embryogenesis. In this stud...
Embryo, Mammalian Machine Learning Transcriptome Embryonic Development Animals Single-Cell Analysis Gene Expression Profiling Mice Support Vector Machine
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CaSTLe - Classification of single cells by transfer learning: Harnessing the power of publicly available single cell RNA sequencing experiments to annotate new experiments.

PloS one Oct 10, 2018
Single-cell RNA sequencing (scRNA-seq) is an emerging technology for profiling the gene expression of thousands of cells at the single cell resolution. Currently, the labeling of cells in an scRNA-seq dataset is performed by manually characterizing c...
Retina Hematopoietic Stem Cells Embryo, Mammalian Humans Single-Cell Analysis Datasets as Topic Machine Learning Mice Pancreas Animals Sequence Analysis, RNA Time Factors Access to Information
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