AIMC Topic: Cryopreservation
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The effect of cryopreservation on enamel microcracks - A μCT analysis using a deep learning algorithm.
Cryobiology
Mar 13, 2025
To date, the effect of cryopreservation on microcracks in the dental enamel remains unclear. These enamel microcracks are very thin, at the limit of visibility and their segmentation is beyond the capabilities of traditional image analysis. The objec...
Comparison of Individualized Rescue Luteal Phase Support Strategies with Vaginal and Combined Vaginal & Subcutaneous Progesterone Administration in Artificial Frozen-Thawed Blastocyst Embryo Transfer Cycles Based on Serum Progesterone levels.
Frontiers in endocrinology
Jan 17, 2025
OBJECTIVES: Hormone replacement therapy (HRT) frozen embryo transfer (FET) cycles are common in assisted reproductive techniques. As the corpus luteum is absent in these cycles, luteal phase support is provided by administering progesterone (P4) thro...
An explainable ultrasound-based machine learning model for predicting reproductive outcomes after frozen embryo transfer.
Reproductive biomedicine online
Nov 28, 2024
RESEARCH QUESTION: Can an optimal machine learning model be developed to predict reproductive outcomes following frozen embryo transfer (FET)?
Improved clinical pregnancy rates in natural frozen-thawed embryo transfer cycles with machine learning ovulation prediction: insights from a retrospective cohort study.
Scientific reports
Nov 27, 2024
This study aims to develop physician support software for determining ovulation time and assess its impact on pregnancy outcomes in natural cycle frozen embryo transfers (NC-FET). To develop, assess, and validate an ovulation prediction model, three ...
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?
Quality assurance (QA) for monitoring the performance of assisted reproductive technology (ART) staff using artificial intelligence (AI).
Journal of assisted reproduction and genetics
Nov 14, 2022
PURPOSE: Deep learning neural networks have been used to predict the developmental fate and implantation potential of embryos with high accuracy. Such networks have been used as an assistive quality assurance (QA) tool to identify perturbations in th...
Correlation between an annotation-free embryo scoring system based on deep learning and live birth/neonatal outcomes after single vitrified-warmed blastocyst transfer: a single-centre, large-cohort retrospective study.
Journal of assisted reproduction and genetics
Jul 26, 2022
PROPOSE: Does an annotation-free embryo scoring system based on deep learning and time-lapse sequence images correlate with live birth (LB) and neonatal outcomes?
Pregnancy prediction performance of an annotation-free embryo scoring system on the basis of deep learning after single vitrified-warmed blastocyst transfer: a single-center large cohort retrospective study.
Fertility and sterility
Jul 8, 2021
OBJECTIVE: To analyze the performance of an annotation-free embryo scoring system on the basis of deep learning for pregnancy prediction after single vitrified blastocyst transfer (SVBT) compared with the performance of other blastocyst grading syste...
Humans
Retrospective Studies
Pregnancy
Female
Adult
Middle Aged
Deep Learning
Heart Rate, Fetal
Maternal Age
Embryo Culture Techniques
Time-Lapse Imaging
Infertility
Single Embryo Transfer
Vitrification
Embryo Implantation
Predictive Value of Tests
Blastocyst
Pregnancy Rate
Image Interpretation, Computer-Assisted
Cryopreservation
Fertilization in Vitro
Treatment Outcome
Embryo selection with artificial intelligence: how to evaluate and compare methods?
Journal of assisted reproduction and genetics
Jun 26, 2021
Embryo selection within in vitro fertilization (IVF) is the process of evaluating qualities of fertilized oocytes (embryos) and selecting the best embryo(s) available within a patient cohort for subsequent transfer or cryopreservation. In recent year...
High spatially sensitive quantitative phase imaging assisted with deep neural network for classification of human spermatozoa under stressed condition.
Scientific reports
Aug 4, 2020
Sperm cell motility and morphology observed under the bright field microscopy are the only criteria for selecting a particular sperm cell during Intracytoplasmic Sperm Injection (ICSI) procedure of Assisted Reproductive Technology (ART). Several fact...
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