AIMC Topic: Embryonic Development
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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...
Artificial intelligence (AI)-driven morphological assessment of zebrafish larvae for developmental toxicity chemical screening.
Aquatic toxicology (Amsterdam, Netherlands)
May 20, 2025
Screening chemicals using the zebrafish embryo developmental toxicity assay requires visual assessment of larval morphological changes based on images by experienced screeners. The process is time-consuming and prone to subjectivity. However, deep le...
Integrating genetic variation with deep learning provides context for variants impacting transcription factor binding during embryogenesis.
Genome research
May 2, 2025
Understanding how genetic variation impacts transcription factor (TF) binding remains a major challenge, limiting our ability to model disease-associated variants. Here, we used a highly controlled system of F crosses with extensive genetic diversity...
Multi-omics analyses and machine learning prediction of oviductal responses in the presence of gametes and embryos.
eLife
Feb 26, 2025
The oviduct is the site of fertilization and preimplantation embryo development in mammals. Evidence suggests that gametes alter oviductal gene expression. To delineate the adaptive interactions between the oviduct and gamete/embryo, we performed a m...
Learning-based inference of longitudinal image changes: Applications in embryo development, wound healing, and aging brain.
Proceedings of the National Academy of Sciences of the United States of America
Feb 20, 2025
Longitudinal imaging data are routinely acquired for health studies and patient monitoring. A central goal in longitudinal studies is tracking relevant change over time. Traditional methods remove nuisance variation with custom pipelines to focus on ...
X-scPAE: An explainable deep learning model for embryonic lineage allocation prediction based on single-cell transcriptomics revealing key genes in embryonic cell development.
Computers in biology and medicine
Feb 12, 2025
In single-cell transcriptomics research, accurately predicting cell lineage allocation and identifying differences between lineages are crucial for understanding cell differentiation processes and reducing early pregnancy miscarriages in humans. This...
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 ...
The regulatory landscape of 5' UTRs in translational control during zebrafish embryogenesis.
Developmental cell
Jan 15, 2025
The 5' UTRs of mRNAs are critical for translation regulation during development, but their in vivo regulatory features are poorly characterized. Here, we report the regulatory landscape of 5' UTRs during early zebrafish embryogenesis using a massivel...
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...
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