Secure cloud-based medical history management with deep learning integration

Abstract

Author(s): J. Preethi, Kotari Sridevi, Pakkiru Sony, Vanaja Nakka, K Vaishali, Swamy Gachikanti

In the modern healthcare landscape, ensuring accurate and efficient access to patient medical history is crucial for effective treatment. This paper presents a cloud-based system that assigns a unique ID to each patient, securely storing and managing their medical records. The system leverages advanced deep learning models to enhance data consistency, identify duplicate patients, and support robust analysis of medical history. By utilizing industry-standard encryption and authentication methods, the system ensures the privacy and security of patient data. The adoption of cloud technologies facilitates seamless organization, tracking, and retrieval of vast amounts of patient data. Additionally, the integration of deep learning models enables healthcare providers to derive insights from medical histories, improving patient outcomes. The results demonstrate that the system not only enhances collaboration among healthcare providers but also supports real-time, secure access to comprehensive medical history records, ultimately improving the quality of care.

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