March 3, 2025

Privacy-Preserving AI Models for Secure Healthcare Data in the Cloud

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This paper demonstrates improved data security in cloud healthcare systems using AI privacy methods, suggesting efficiency gains.

Privacy-preserving techniques enable secure cloud-based healthcare analytics, facilitating real-time data management.
The hybrid framework integrates homomorphic encryption, differential privacy, and federated learning to enhance patient data security.
Using 50,000 anonymized patient histories, the study validated models for prediction accuracy and compliance with privacy regulations.
Healthcare analytics may enable effective decision-making while ensuring ethical handling of sensitive patient information.

Abhishek Reddy (2025) studied this question.

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