Enhancing predictive models for egg donation: time to blastocyst hatching and machine learning insights.

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.

Methods

Multicenter retrospective cohort study carried out in 378 egg donor recipients who performed a fresh single embryo transfer during 2021. All treatments were performed by Intracytoplasmic Sperm Injection, using fresh or frozen oocytes. The embryos were cultured in Geri

SUBMITTER: Ten J 

PROVIDER: S-EPMC11389240 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature