Next Generation Healthcare Systems on Cloud Leveraging AI for Adaptive Decision Making and Risk Management
DOI:
https://doi.org/10.15662/IJEETR.2025.0704013Keywords:
Cloud computing, artificial intelligence, healthcare systems, adaptive decision-making, risk management, predictive analytics, electronic health records, telemedicine, clinical data processing, patient safetyAbstract
The healthcare sector is experiencing a paradigm shift with the adoption of cloud computing and artificial intelligence (AI) to support adaptive decision-making and effective risk management. This study proposes a next-generation healthcare system architecture that integrates cloud infrastructure with AI-driven analytics to process large-scale clinical data, enhance patient care, and proactively manage healthcare risks. By leveraging cloud scalability, healthcare providers can store and process extensive electronic health records, medical imaging, and real-time patient monitoring data efficiently. AI algorithms, including machine learning and deep learning models, facilitate predictive diagnostics, personalized treatment planning, and early detection of potential medical complications. The proposed system also incorporates automated risk management mechanisms, monitoring operational, clinical, and financial risks to ensure patient safety and regulatory compliance. Preliminary evaluations indicate significant improvements in decision-making speed, predictive accuracy, resource allocation, and risk mitigation compared to conventional healthcare IT systems. The integration of cloud computing and AI not only streamlines healthcare workflows but also supports telemedicine, remote monitoring, and population health management. This research contributes to the development of intelligent, secure, and adaptive healthcare systems, offering a scalable solution for modern medical institutions navigating complex clinical and operational challenges.
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