Cloud-Based Healthcare Analytics Platform
DOI:
https://doi.org/10.5281/ijurd.v1i4.42Keywords:
Cloud Computing, Big Data, Healthcare Analytics, Hadoop, Scalable SystemsAbstract
The rapid growth of healthcare data has created a need for scalable and efficient platforms capable of handling large volumes of heterogeneous medical information. This paper presents a Cloud-Based Healthcare Analytics Platform designed to support data storage, processing, and real-time analysis for improved clinical decision-making. The proposed system leverages cloud computing technologies to provide on-demand resources, enabling efficient handling of electronic health records, medical images, and patient-generated data. Machine learning and data mining techniques are integrated into the platform to extract meaningful insights, support disease prediction, and enhance clinical decision support systems. The framework also incorporates data security mechanisms such as encryption and access control to ensure patient privacy and regulatory compliance. Additionally, the platform enables interoperability and seamless data sharing across healthcare systems. Experimental observations indicate that the proposed solution improves scalability, reduces computational overhead, and enhances analytical performance compared to traditional systems. The study highlights the potential of cloud-based analytics platforms in transforming healthcare delivery through efficient, cost-effective, and scalable data-driven solutions.
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Copyright (c) 2025 Alok Shah, Sneha Verma
This work is licensed under a Creative Commons Attribution 4.0 International License.
