Comparing performance between clinics of an embryo evaluation algorithm based on time-lapse images and machine learning.

Martin Nygaard JohansenErik T ParnerMikkel F KraghKeiichi KatoSatoshi UenoStefan PalmManuel KernbachBaşak Balabanİpek KeleşAnette V GabrielsenLea H IversenJørgen Berntsen

Published in: Journal of assisted reproduction and genetics (2023)

The method of using age-standardization of the AUCs that is proposed in this article mitigates some of the variability between clinics. This enables a comparison of clinic-specific AUCs where the difference in age distributions is accounted for.

Keyphrases

machine learning
primary care
deep learning
artificial intelligence
convolutional neural network
optical coherence tomography
radiation therapy
neural network
monte carlo