deepBlastoid: A deep learning model for automated and efficient evaluation of human blastoids
Peer-Reviewed Publication
Updates every hour. Last Updated: 2-Apr-2026 21:15 ET (3-Apr-2026 01:15 GMT/UTC)
Researchers from King Abdullah University of Science and Technology (KAUST) have developed deepBlastoid, the first deep-learning platform specifically designed for the high-throughput, automated classification of human stem cell-derived embryo models (blastoids). By leveraging a ResNet-18 architecture and a novel Confidence Rate metric, the model achieves up to 97% accuracy and processes images 1,000 times faster than human experts. This tool facilitates large-scale drug screening and basic research into early human development by providing a standardized, objective evaluation framework.
As an emerging branch of clinical medicine, microbiota medicine has attracted worldwide attention from clinicians, medical educators, patient communities, and industry. However, this developing field still lacks consensus on its fundamental principles as well as guidelines for clinical and educational practice. An expert panel was convened by the journal Microbiota Medicine Research at the 2025 CHINAGUT Conference to develop the principles and practice guidelines of microbiota medicine.