Digital healthcare ecosystem AI optimization for privacy-centric federated analytics
Keywords:
Artificial Intelligence, federated analytics, privacy-preserving, federated learningAbstract
Growing digital healthcare ecosystems need privacy-preserving technologies to secure patient data. Federated analytics allows privacy and collaboration by analyzing data across decentralized systems without transferring raw data. Federation analytics and AI may enhance privacy-centric healthcare AI systems, says one research. Per GDPR and HIPAA, FL allows AI manage healthcare data without centralized repositories. Data heterogeneity, model convergence, and privacy in machine learning-based federated healthcare analytics are examined. AI-driven federated learning in healthcare may provide scalable, privacy-preserving insights, according to case studies. Efficiency and performance are improved by our approaches. The article recommends federated healthcare ecosystems use explainable AI (XAI) and advanced encryption to promote privacy and model transparency.
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