Research

Development of an artificial intelligence-based assessment model for prediction of embryo viability using static images captured by optical light microscopy during IVF

Authors: M VerMilyea, JMM Hall, S. Diakiw, A Johnston, T Nguyen, D Perugini, A Miller, A Picou, AP Murphy, M Perugini

Title: Development of an artificial intelligence-based assessment model for prediction of embryo viability using static images captured by optical light microscopy during IVF

Authors: M VerMilyea, JMM Hall, S. Diakiw, A Johnston, T Nguyen, D Perugini, A Miller, A Picou, AP Murphy, M Perugini

Objective: Can an artificial intelligence (AI)-based model predict human embryo viability using images captured by optical light microscopy?

Published: Human Reproduction, deaa013

Why This Research Helps Patients:

Embryo selection following IVF is a critical factor in determining the success of ensuing pregnancy. Traditional morphokinetic grading by trained embryologists can be subjective and variable, and other complementary techniques, such as time-lapse imaging, require costly equipment and have not reliably demonstrated predictive ability for the endpoint of clinical pregnancy. AI methods are being investigated as a promising means for improving embryo selection and predicting implantation and pregnancy outcomes.