Abstract            Volume:10  Issue-8  Year-2022         Original Research Articles

Online ISSN : 2347 - 3215 Issues : 12 per year Publisher : Excellent Publishers Email : editorijcret@gmail.com

The integration of Artificial Intelligence (AI) and cloud technologies in healthcare data management has the potential to transform the industry by enhancing operational efficiency, improving patient care, and streamlining healthcare processes. This paper proposes a novel AI-driven system that leverages cloud computing and Natural Language Processing (NLP) to automate the management of healthcare data, including Electronic Health Records (EHRs), medical imaging, and patient records. The proposed system aims to address key challenges in healthcare, such as data security, integration with legacy systems, and data interoperability, while improving accuracy and reducing operational costs. Through the use of AI models, the system can extract actionable insights from unstructured medical data, automate routine workflows like appointment scheduling and patient follow-ups, and provide real-time decision support to healthcare professionals. Cloud storage ensures scalable and secure management of large healthcare datasets, while NLP techniques enable efficient data extraction from medical texts. The system was evaluated based on several performance metrics, including accuracy, efficiency, cost savings, and patient satisfaction, demonstrating a significant improvement over existing method. Results indicate that the proposed AI-driven system outperforms traditional healthcare systems in accuracy, processing time, and patient satisfaction. However, challenges such as AI integration with existing infrastructures and data privacy concerns remain. Future work will focus on refining the system, addressing these challenges, and expanding its application across various healthcare domains to optimize operations and enhance patient care.

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