Robust Automated Assessment of Human Blastocyst Quality using Deep Learning
Pegah Khosravi, Ehsan Mohamad Kazemi, Qiansheng Zhan, Marco Toschi, Jonas E. Malmsten, Cristina Fontes Lindemann Hickman, Marcos Meseguer, Zev Rosenwaks, Olivier Elemento, Nikica Zaninović, Iman Hajirasouliha
This paper develops an AI system to assess human blastocyst quality using deep learning, achieving 98% accuracy and identifying clinical factors affecting pregnancy rates.
bioRxiv · Aug 20, 2018 · PreprintBioinformatics