Training a machine learning model to assess embryo characteristics from video image data

Abstract

A method for training a computer-based machine learning model to assess a characteristics-of-interest in embryos such as viability, sex or genetic superiority/inferiority by processing video of each of a plurality of embryos and wherein a subset of the embryos each embodies the characteristic-of-interest. The method includes obtaining (taking or otherwise procuring) a plurality of training videos, each video being of a target embryo and each video having a real-time frame speed (specifically not time-lapse frame speed) over a continuous recording duration of ten minutes or less. Each video includes image data representing micro-movement of the target embryo. The image data is processed thereby generating a computer-based machine learning model for assessing the characteristic-of-interest in future embryos from image data of those embryos.