Cloud-Based Healthcare Data Analytics for Disease Prediction
Abstract
Healthcare organizations generate massive volumes of patient data that require efficient processing and analysis. This paper proposes a cloud-based healthcare analytics framework for disease prediction using machine learning algorithms and distributed cloud infrastructure. The system analyzes patient medical records, diagnostic reports, and real-time sensor data to identify potential health risks. Experimental results demonstrate improved prediction accuracy, faster data processing, and enhanced accessibility for healthcare professionals. The study concludes that cloud-enabled healthcare analytics can significantly improve preventive healthcare and clinical decision-making.
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