Lomas de Chapultepec

Abstract Research question : Using a novel artificial vision-based software (SiD V1.0; IVF 2.0, UK), we aimed to explore a correlation between individual sperm kinematics evaluated in real-time and spermatozoa selected by an embryologist for intracytoplasmic sperm injection (ICSI), with subsequent normal fertilization and blastocyst formation. Design : ICSI procedures were randomly video recorded and subjected to analysis using SiD V1.0, proprietary software developed by our group.

Abstract 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 selecting an embryo for transfer. Morphological assessment of embryos is the traditional method of evaluating embryo quality and selecting which embryo to transfer.

Abstract Research question Can a deep machine learning artificial intelligence algorithm predict ploidy and implantation in a known data set of static blastocyst images, and how does its performance compare against chance and experienced embryologists? Design A database of blastocyst images with known outcome was applied with an algorithm dubbed ERICA (embryo ranking intelligent classification algorithm).