An interpretable machine learning model for predicting the optimal day of trigger during ovarian stimulation
An interpretable machine learning model for predicting the optimal day of trigger during ovarian stimulation
May 16th, 2022
Michael Fanton, Ph.D. | Veronica I. Nutting, B.A. | Funmi Solano | Paxton Maeder-York, M.S., M.B.A. | Eduardo Hariton, M.D., M.B.A. | Oleksii O. Barash, Ph.D. | Louis N. Weckstein, M.D | Denny Sakkas, Ph.D. | Alan B. Copperman, M.D. | Kevin E. Loewke, Ph.D.
Abstract
Objective: To develop an interpretable machine learning model for optimizing the day of trigger in terms of mature oocytes (MII), fertilized oocytes (2PNs), and usable blastocysts.
Design: Retrospective study.
Setting: A group of three assisted reproductive technology centers in the United States.
Patient(s): Patients undergoing autologous in vitro fertilization cycles from 2014 to 2020 (n = 30,278).
DOI:https://doi.org/10.1016/j.fertnstert.2022.04.003