AIMC Topic: Oocytes
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Machine learning and microfluidic integration for oocyte quality prediction.
Scientific reports
Jul 22, 2025
Despite advancements in in vitro fertilization (IVF) over the past 30 years, its outcome effectiveness remains low (20-40%). This study introduces a microfluidic-based machine learning framework to improve predictive accuracy in oocyte quality assess...
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...
Automated detection and recognition of oocyte toxicity by fusion of latent and observable features.
Journal of hazardous materials
Apr 26, 2025
Oocyte quality is essential for successful pregnancy, yet no discriminant criterion exists to assess the effects of environmental pollutants on oocyte abnormalities. We developed a stepwise framework integrating deep learning-extracted latent feature...
Fluo-Cast-Bright: a deep learning pipeline for the non-invasive prediction of chromatin structure and developmental potential in live oocytes.
Communications biology
Jan 29, 2025
In mammalian oocytes, large-scale chromatin organization regulates transcription, nuclear architecture, and maintenance of chromosome stability in preparation for meiosis onset. Pre-ovulatory oocytes with distinct chromatin configurations exhibit pro...
Explainable artificial intelligence to identify follicles that optimize clinical outcomes during assisted conception.
Nature communications
Jan 8, 2025
Infertility affects one-in-six couples, often necessitating in vitro fertilization treatment (IVF). IVF generates complex data, which can challenge the utilization of the full richness of data during decision-making, leading to reliance on simple 'ru...
Identification of diagnostic genes and the miRNA‒mRNA‒TF regulatory network in human oocyte aging via machine learning methods.
Journal of assisted reproduction and genetics
Nov 14, 2024
PURPOSE: Oocyte aging is a significant factor in the negative reproductive outcomes of older women. However, the pathogenesis of oocyte aging remains unclear. This study aimed to identify the hub genes involved in oocyte aging via bioinformatics meth...
A review of artificial intelligence applications in in vitro fertilization.
Journal of assisted reproduction and genetics
Oct 14, 2024
The field of reproductive medicine has witnessed rapid advancements in artificial intelligence (AI) methods, which have significantly enhanced the efficiency of diagnosing and treating reproductive disorders. The integration of AI algorithms into the...
On the role of artificial intelligence in analysing oocytes during in vitro fertilisation procedures.
Artificial intelligence in medicine
Oct 8, 2024
Nowadays, the most adopted technique to address infertility problems is in vitro fertilisation (IVF). However, its success rate is limited, and the associated procedures, known as assisted reproduction technology (ART), suffer from a lack of objectiv...
Machine learning tool for predicting mature oocyte yield and trigger day from start of stimulation: towards personalized treatment.
Reproductive biomedicine online
Sep 4, 2024
RESEARCH QUESTION: Can machine learning tools predict the number of metaphase II (MII) oocytes and trigger day at the start of the ovarian stimulation cycle?
Looking into the future: a machine learning powered prediction model for oocyte return rates after cryopreservation.
Reproductive biomedicine online
Aug 29, 2024
RESEARCH QUESTION: Could a predictive model, using data from all US fertility clinics reporting to the Society for Assisted Reproductive Technology, estimate the likelihood of patients using their stored oocytes?
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