Health Condition Prediction and the Role of Cloud-Based Environments

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Dennis Ssebugulu

Abstract

Recently, there has been interest towards the adoption of cloud-enabled big data applications as an ideal means through which unstructured and structured data arising from systems of healthcare management could be analyzed. The main aim of this study was to establish a mechanism for probabilistic data collection, which would transform into the performance of the collected data’s correction analysis. Also, the study sought to develop a stochastic prediction framework towards predicting future health conditions among patients. The prediction model would be implemented in a way that focused on the current health status of the selected subjects. With cloud environments’ extension simulations, there was the evaluation of the proposed system. In the findings, it maintained bandwidth utilization and 90% CPU. It also achieved a prediction accuracy of 98%, superior outcomes that led to a significant reduction in the time of analysis.

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