AI Medical Compendium Journal:
Reproductive biomedicine online

Showing 21 to 30 of 37 articles

Association between a deep learning-based scoring system with morphokinetics and morphological alterations in human embryos.

Reproductive biomedicine online
RESEARCH QUESTION: What is the association between the deep learning-based scoring system, iDAScore, and biological events during the pre-implantation period?

An artificial intelligence model correlated with morphological and genetic features of blastocyst quality improves ranking of viable embryos.

Reproductive biomedicine online
RESEARCH QUESTION: Can better methods be developed to evaluate the performance and characteristics of an artificial intelligence model for evaluating the likelihood of clinical pregnancy based on analysis of day-5 blastocyst-stage embryos, such that ...

Evaluation of oocyte maturity using artificial intelligence quantification of follicle volume biomarker by three-dimensional ultrasound.

Reproductive biomedicine online
RESEARCH QUESTION: Can a novel deep learning-based follicle volume biomarker using three-dimensional ultrasound (3D-US) be established to aid in the assessment of oocyte maturity, timing of HCG administration and the individual prediction of ovarian ...

Comparison of machine learning classification techniques to predict implantation success in an IVF treatment cycle.

Reproductive biomedicine online
RESEARCH QUESTION: Which machine learning model predicts the implantation outcome better in an IVF cycle? What is the importance of each variable in predicting the implantation outcome in an IVF cycle?

Can the combination of time-lapse parameters and clinical features predict embryonic ploidy status or implantation?

Reproductive biomedicine online
RESEARCH QUESTION: Can models based on artificial intelligence predict embryonic ploidy status or implantation potential of euploid transferred embryos? Can the addition of clinical features into time-lapse monitoring (TLM) parameters as input data i...

Artificial intelligence in the embryology laboratory: a review.

Reproductive biomedicine online
The goal of an IVF cycle is a healthy live-born baby. Despite the many advances in the field of assisted reproductive technologies, accurately predicting the outcome of an IVF cycle has yet to be achieved. One reason for this is the method of selecti...

An artificial intelligence platform to optimize workflow during ovarian stimulation and IVF: process improvement and outcome-based predictions.

Reproductive biomedicine online
RESEARCH QUESTION: Can workflow during IVF be facilitated by artificial intelligence to limit monitoring during ovarian stimulation to a single day and enable level-loading of retrievals?

Will the introduction of automated ART laboratory systems render the majority of embryologists redundant?

Reproductive biomedicine online
IVF techniques have changed over time with the aim of improving clinical results. Today, embryology is facing a change common to most areas of medicine, the introduction of automation. The use of automated systems in the IVF laboratory is already hap...

Inter-centre reliability in embryo grading across several IVF clinics is limited: implications for embryo selection.

Reproductive biomedicine online
RESEARCH QUESTION: What is the intra- and inter-centre reliability in embryo grading performed according to the Istanbul Consensus across several IVF clinics?