Can artificial intelligence guided feedback improve embryologists' selection of euploid embryos based on morphology alone?

Can embryologists reliably differentiate euploid from aneuploid embryos based on morphology alone, and can artificial intelligence (AI)-assisted selection, specifically using ERICA (Embryo Ranking Intelligent Classification Algorithm), improve embryo selection outcomes compared with embryologists alone? A training tool was developed and used in which 19 embryologists (comprising junior, intermediate and experienced practitioners) evaluated the ploidy status of embryo images. They were subsequently provided with rankings generated by ERICA for the same embryos and asked to make a final judgment combining both sources of information. Each embryologist conducted this process on between 20 to 150 simulated IVF cycles to assess performance in identifying euploid embryos. Both embryologists and ERICA demonstrated a statistically significant ability to identify aneuploidy better than random selection (both P < 0.001). ERICA outperformed embryologists in selecting euploid embryos on the first attempt (P = 0.002). No significant difference was observed between groups of embryologists in picking a better or worse embryo and, given the opportunity to change their mind in the light of the ERICA output, there was no significant change for the better or worse, despite a large number changing their minds. The study highlights that AI tools like ERICA can enhance the reliability of embryo selection by reducing subjectivity and bias; however, the combination of human and AI judgment does not always provide a clear advantage over using either method independently. These findings emphasize the need to better understand the influence of AI on human decision-making and the trust placed in automated processes in IVF settings. [Abstract copyright: Copyright © 2025 The Author(s). Published by Elsevier Ltd.. All rights reserved.]