AIMC Topic: Blastocyst
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Development and validation of machine learning models for predicting blastocyst yield in IVF cycles.
Scientific reports
Jul 2, 2025
Predicting blastocyst formation poses significant challenges in reproductive medicine and critically influences clinical decision-making regarding extended embryo culture. While previous research has primarily focused on determining whether an IVF cy...
Artificial intelligence outperforms humans in morphology-based oocyte selection in cattle.
Scientific reports
Jul 1, 2025
Evaluating cumulus-oocyte complex (COC) morphology is commonly used to assess oocyte quality. However, clear guidelines on interpreting COC morphology data are lacking as this evaluation method is subjective. In the present study, individual in vitro...
Application of a methodological framework for the development and multicenter validation of reliable artificial intelligence in embryo evaluation.
Reproductive biology and endocrinology : RB&E
Jan 31, 2025
BACKGROUND: Artificial intelligence (AI) models analyzing embryo time-lapse images have been developed to predict the likelihood of pregnancy following in vitro fertilization (IVF). However, limited research exists on methods ensuring AI consistency ...
Challenges in standardizing preimplantation kidney biopsy assessments and the potential of AI-Driven solutions.
Current opinion in nephrology and hypertension
Jan 20, 2025
PURPOSE OF REVIEW: This review explores the variability in preimplantation kidney biopsy processing methods, emphasizing their impact on histological interpretation and allocation decisions driven by biopsy findings. With the increasing use of artifi...
A novel deep learning approach to identify embryo morphokinetics in multiple time lapse systems.
Scientific reports
Nov 22, 2024
The use of time lapse systems (TLS) in In Vitro Fertilization (IVF) labs to record developing embryos has paved the way for deep-learning based computer vision algorithms to assist embryologists in their morphokinetic evaluation. Today, most of the l...
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...
Enhancing predictive models for egg donation: time to blastocyst hatching and machine learning insights.
Reproductive biology and endocrinology : RB&E
Sep 11, 2024
BACKGROUND: Data sciences and artificial intelligence are becoming encouraging tools in assisted reproduction, favored by time-lapse technology incubators. Our objective is to analyze, compare and identify the most predictive machine learning algorit...
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)?
Deep learning versus manual morphology-based embryo selection in IVF: a randomized, double-blind noninferiority trial.
Nature medicine
Aug 9, 2024
To assess the value of deep learning in selecting the optimal embryo for in vitro fertilization, a multicenter, randomized, double-blind, noninferiority parallel-group trial was conducted across 14 in vitro fertilization clinics in Australia and Euro...
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