AIMC Topic: Embryonic Development
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Deep learning-based models for preimplantation mouse and human embryos based on single-cell RNA sequencing.
Nature methods
Nov 14, 2024
The rapid growth of single-cell transcriptomic technology has produced an increasing number of datasets for both embryonic development and in vitro pluripotent stem cell-derived models. This avalanche of data surrounding pluripotency and the process ...
A deep learning model for predicting blastocyst formation from cleavage-stage human embryos using time-lapse images.
Scientific reports
Nov 14, 2024
Efficient prediction of blastocyst formation from early-stage human embryos is imperative for improving the success rates of assisted reproductive technology (ART). Clinics transfer embryos at the blastocyst stage on Day-5 but Day-3 embryo transfer o...
Can time-lapse culture combined with artificial intelligence improve ongoing pregnancy rates in fresh transfer cycles of single cleavage stage embryos?
Frontiers in endocrinology
Aug 29, 2024
PURPOSE: With the rapid advancement of time-lapse culture and artificial intelligence (AI) technologies for embryo screening, pregnancy rates in assisted reproductive technology (ART) have significantly improved. However, clinical pregnancy rates in ...
Use of federated learning to develop an artificial intelligence model predicting usable blastocyst formation from pre-ICSI oocyte images.
Reproductive biomedicine online
Aug 13, 2024
RESEARCH QUESTION: Can federated learning be used to develop an artificial intelligence (AI) model for evaluating oocyte competence using two-dimensional images of denuded oocytes in metaphase II prior to intracytoplasmic sperm injection (ICSI)?
The construction of machine learning-based predictive models for high-quality embryo formation in poor ovarian response patients with progestin-primed ovarian stimulation.
Reproductive biology and endocrinology : RB&E
Jul 10, 2024
OBJECTIVE: To explore the optimal models for predicting the formation of high-quality embryos in Poor Ovarian Response (POR) Patients with Progestin-Primed Ovarian Stimulation (PPOS) using machine learning algorithms.
Dev-ResNet: automated developmental event detection using deep learning.
The Journal of experimental biology
May 29, 2024
Delineating developmental events is central to experimental research using early life stages, permitting widespread identification of changes in event timing between species and environments. Yet, identifying developmental events is incredibly challe...
DeepFace: Deep-learning-based framework to contextualize orofacial-cleft-related variants during human embryonic craniofacial development.
HGG advances
May 24, 2024
Orofacial clefts (OFCs) are among the most common human congenital birth defects. Previous multiethnic studies have identified dozens of associated loci for both cleft lip with or without cleft palate (CL/P) and cleft palate alone (CP). Although seve...
Segmentation of mature human oocytes provides interpretable and improved blastocyst outcome predictions by a machine learning model.
Scientific reports
May 8, 2024
Within the medical field of human assisted reproductive technology, a method for interpretable, non-invasive, and objective oocyte evaluation is lacking. To address this clinical gap, a workflow utilizing machine learning techniques has been develope...
A novel machine-learning framework based on early embryo morphokinetics identifies a feature signature associated with blastocyst development.
Journal of ovarian research
Mar 15, 2024
BACKGROUND: Artificial Intelligence entails the application of computer algorithms to the huge and heterogeneous amount of morphodynamic data produced by Time-Lapse Technology. In this context, Machine Learning (ML) methods were developed in order to...
A clinical consensus-compliant deep learning approach to quantitatively evaluate human in vitro fertilization early embryonic development with optical microscope images.
Artificial intelligence in medicine
Jan 19, 2024
The selection of embryos is a key for the success of in vitro fertilization (IVF). However, automatic quality assessment on human IVF embryos with optical microscope images is still challenging. In this study, we developed a clinical consensus-compli...
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