STUDY QUESTION: Can an artificial intelligence (AI)-based model predict human embryo viability using images captured by optical light microscopy?
SUMMARY ANSWER: We have combined computer vision image processing methods and deep learning techniques to create the noninvasive Life Whisperer AI model for robust prediction of embryo viability, as measured by clinical pregnancy outcome, using single static images of Day 5 blastocysts obtained from standard optical light microscope systems.
MAIN RESULTS AND THE ROLE OF CHANCE:
Distributions of predictions showed clear separation of correctly and incorrectly classified embryos. Binary comparison of viable/non-viable embryo classification demonstrated an improvement of 24.7% over embryologists’ accuracy (P=0.047, n=2, Student’s t test), and 5-band ranking comparison demonstrated an improvement of 42.0% over embryologists (P=0.028, n=2, Student’s t test).