An AI-Enabled Cloud Framework for Healthcare ERP Targeted Advertising with LLM Analytics and Deep Learning–Based Industrial Effluent Prediction
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Abstract
The digital transformation of healthcare organizations has accelerated the adoption of cloud-based Enterprise Resource Planning (ERP) systems, enabling advanced data utilization for targeted digital advertising. However, the sensitive nature of healthcare data necessitates strong cybersecurity measures and regulatory compliance. This paper proposes an artificial intelligence–enabled framework for targeted digital advertising in cloud-based healthcare ERP systems, integrating LLM-driven analytics with robust cybersecurity assurance. The framework leverages AI and Large Language Models (LLMs) to analyze structured and unstructured ERP data, generate contextual marketing insights, and optimize advertising campaigns with improved precision and relevance. A cloud-based architecture ensures scalability, flexibility, and real-time processing, while cybersecurity mechanisms such as secure data access, encryption, and privacy-preserving analytics protect sensitive information. The proposed approach demonstrates how intelligent analytics combined with secure cloud engineering can enhance advertising effectiveness, decision-making, and trust within healthcare ERP ecosystems.
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