Trusted Medical Data Sharing Framework for Edge Computing: A Review Analysis

Preeti Mahara, Ankur Patney, Nitya Khare — Mon, 06 Apr 2026 00:00:00 +0000

Edge computing is transforming medical data processing by moving computation and storage closer to data sources (wearables, bedside monitors, hospital gateways), reducing latency and bandwidth use while enabling real-time analytics. However, sensitive health data and the distributed, resource-constrained nature of edge environments introduce unique trust, privacy, and interoperability challenges. This review synthesizes the literature on trusted medical data sharing frameworks for edge computing. The author presents a taxonomy of architectural patterns (blockchain/ledger-anchored, attribute-based encryption, federated learning, TEEs, MPC/HE and hybrid stacks), evaluates their security/privacy/performance tradeoffs, identifies practical limitations (scalability, key management, legal compliance), and proposes a prioritized research agenda and engineering best practices. Key conclusions: hybrid architectures that keep PHI local, use privacy-preserving collaborative learning, and record minimal metadata on permissioned ledgers currently offer the best balance for practical deployments, but standard benchmarks, regulatory mapping, and lightweight authorization primitives remain urgent needs.

Artificial Intelligence in Content Creation: Technologies, Applications, and Challenges

Suraj R. Nalawade, Abhishek Sudarshan Kadam — Tue, 12 May 2026 00:00:00 +0000

Artificial intelligence (AI) is significantly transforming the field of content creation by improving creativity, efficiency, and personalization. This study explores the use of advanced AI technologies such as generative adversarial networks (GANs), large language models (LLMs), diffusion models, and multimodal systems in generating text, images, audio, and video content. AI tools are widely used in industries including marketing, journalism, education, entertainment, and e-commerce to automate repetitive tasks, enhance user engagement, and reduce production costs. The study also highlights the growing importance of AI-human collaboration, where AI supports creators in brainstorming, editing, and designing content rather than replacing them. Emerging applications such as virtual influencers, synthetic media, and adaptive storytelling are reshaping digital communication. However, challenges such as misinformation, algorithmic bias, intellectual property rights, and trust remain critical concerns. The study concludes that AI has the potential to redefine creative industries when applied responsibly with proper ethical guidelines, transparency, and human oversight. Future developments in emotionally intelligent and immersive AI systems are expected to further expand content creation possibilities.

Journal of Innovations in Data Science and Big Data Management

Trusted Medical Data Sharing Framework for Edge Computing: A Review Analysis

Artificial Intelligence in Content Creation: Technologies, Applications, and Challenges