An integrated shuffler optimizes the privacy of personal genomic data used for machine learning
By integrating an ensemble of privacy-preserving algorithms, a KAUST research team has developed a machine-learning approach that addresses a significant challenge in medical research: How to use the power of artificial intelligence ...
Feb 15, 2024
0
49