September 16, 2025Open Access

Framework for Government Policy on Agentic and Generative AI in Healthcare: Governance, Regulation, and Risk Management of Open-Source and Proprietary Models

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SJSatyadhar JoshiBar-Ilan University

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Implication

Comprehensive analysis identifies implementation challenges and risk management in AI healthcare applications, suggesting strategies to balance safety and innovation.

Key Points

Open-source models in healthcare enhance transparency and data privacy, but proprietary systems excel in reliability.
Agentic generative AI has the potential to improve diagnostics and operational efficiency, yet it poses significant risks.
Our framework proposes adaptive policymaking and international standards to address the complexities of AI deployment in healthcare.
Healthcare organizations can benefit from a balanced approach to AI adoption, leveraging both model types for effective risk management.

Cite This Study

Satyadhar Joshi (2025) studied this question.

synapsesocial.com/papers/68d43b18713b0b5dfea7bb4c https://doi.org/10.20944/preprints202509.1087.v1

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Implication

Comprehensive analysis identifies implementation challenges and risk management in AI healthcare applications, suggesting strategies to balance safety and innovation.

Framework for Government Policy on Agentic and Generative AI in Healthcare: Governance, Regulation, and Risk Management of Open-Source and Proprietary Models

Discussion

Member takes

Implication

Key Points

Cite This Study

Framework for Government Policy on Agentic and Generative AI in Healthcare: Governance, Regulation, and Risk Management of Open-Source and Proprietary Models

Discussion

Member takes

Implication

Key Points

Cite This Study

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