Accurate machine learning model for human embryo morphokinetic stage detection.

ABSTRACT:

Purpose

The ability to detect, monitor, and precisely time the morphokinetic stages of human pre-implantation embryo development plays a critical role in assessing their viability and potential for successful implantation. Therefore, there is a need for accurate and accessible tools to analyse embryos. This work describes a highly accurate, machine learning model designed to predict 17 morphokinetic stages of pre-implantation human development, an improvement on existing models. This model provides a robust tool for researchers and clinicians, enabling the automation of morphokinetic stage prediction, standardising the process, and reducing subjectivity between clinics.

Method

A computer vision model was built on a publicly available dataset for embryo Morphokinetic stage de

SUBMITTER: Misaghi H 

PROVIDER: S-EPMC12640390 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature