Design of a Secure SAP-Enabled Cloud Framework Using Generative AI and GANs for Healthcare Incrementality Analytics
DOI:
https://doi.org/10.15662/IJRAI.2025.0805012Keywords:
Generative AI, GANs, SAP cloud framework, healthcare analytics, incrementality testing, secure cloud architecture, data governanceAbstract
The increasing adoption of data-driven decision-making in healthcare has intensified the need for secure, scalable, and intelligent analytical frameworks capable of accurately measuring intervention effectiveness. This paper proposes the design of a secure SAP-enabled cloud framework that leverages Generative Artificial Intelligence (AI) and Generative Adversarial Networks (GANs) to support incrementality analytics in healthcare systems. The proposed architecture integrates heterogeneous healthcare data sources within a cloud-native SAP environment, enabling secure data ingestion, governance, and high-performance analytics. Generative AI models are employed to simulate counterfactual scenarios, while GANs enhance data augmentation and bias mitigation for robust incrementality testing. Security is enforced through a zero-trust approach incorporating encryption, identity-aware access control, and continuous compliance monitoring to address regulatory requirements such as HIPAA and GDPR. Experimental analysis demonstrates improved accuracy in treatment impact assessment and campaign effectiveness evaluation compared to traditional statistical approaches. The framework provides a scalable foundation for trustworthy and intelligent healthcare analytics in cloud-based enterprise environments.
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