Enhancing predictive models for egg donation: time to blastocyst hatching and machine learning insights.
Journal:
Reproductive biology and endocrinology : RB&E
PMID:
39261843
Abstract
BACKGROUND: Data sciences and artificial intelligence are becoming encouraging tools in assisted reproduction, favored by time-lapse technology incubators. Our objective is to analyze, compare and identify the most predictive machine learning algorithm developed using a known implantation database of embryos transferred in our egg donation program, including morphokinetic and morphological variables, and recognize the most predictive embryo parameters in order to enhance IVF treatments clinical outcomes.