Researchers have innovated a privacy-preserving machine-learning method for genomic research, balancing data privacy with AI model performance. Their approach, using a decentralized shuffling algorithm, showcases enhanced efficiency and security, underscoring the critical need for privacy in biomedical data analysis.Credit: 2024 KAUST; Heno Hwang
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