Improving IVF Utilization with Patient-Centric Artificial Intelligence-Machine Learning (AI/ML): A Retrospective Multicenter Experience.

In vitro fertilization (IVF) has the potential to give babies to millions more people globally, yet it continues to be underutilized. We established a globally applicable and locally adaptable IVF prognostics report and framework to support patient-provider counseling and enable validated, data-driven treatment decisions. This study investigates the IVF utilization rates associated with the usage of machine learning, center-specific (MLCS) prognostic reports (the Univfy report) in provider-patient pre-treatment and IVF counseling.

An artificial intelligence tool predicts blastocyst development from static images of fresh mature oocytes.

Research Question: Can a deep learning image analysis model be developed to assess oocyte quality by predicting blastocyst development from images of denuded mature oocytes?

Design: A deep learning model was developed utilizing 37,133 static oocyte images with associated laboratory outcomes from eight fertility clinics (six countries). A subset of data (n = 7807) was allocated to test model performance. External model validation was conducted to assess generalizability and robustness on new data (n = 12,357) from two fertility clinics (two countries).

A novel system for rapid conversion of Gardner embryo grades to linear scale numeric variables.

Research Question: Can Gardner embryo grades be converted to numeric interval variables to improve the incorporation of embryo grading in statistical analyses?

Design: An equation that can be used to convert Gardner embryo grades to regular interval scale variables was developed: the numerical embryo quality scoring index (NEQsi). The NEQsi system was then validated with a retrospective chart analysis assessing IVF cycles (n = 1711) conducted at a single Canadian fertility centre between 2014 and 2022. Gardner embryo grades on file were assigned using EmbryoScope and converted to NEQsi scores.

Preimplantation genetic testing for aneuploidy in patients with low embryo numbers: benefit or harm?

Purpose: We sought to explore the utility of preimplantation genetic testing for aneuploidy (PGT-A) in a poor prognosis group of women with few embryos available for transfer.

Methods: This was a retrospective matched cohort study examining records for first or second-cycle IVF patients with 1 to 3 blastocysts. The study group comprised 130 patients who underwent PGT-A on all embryos.