Abstract
Background: The rapid growth of data in the healthcare domain is a great challenge for traditional data management system for handling and processing such a huge volume of data. The massive growth of data is inevitable and there arises a quest for identifying an effective storage mechanism which can handle vast dynamic data. The advances in technology have paved way for a solution by means of cloud storage. In the current scenario, Cardio Vascular Disease is the major cause of human mortality across the world. This analysis is the hardcore need in today’s medical research for prediction of Cardio Vascular Disease.
Methods: Hence, in this paper, the Heart Disease dataset is taken for analysis. Various experiments have been carried out with the dataset to compare the performance of classification algorithms and Support Vector Machine is found to outperform other algorithms.
Conclusion: Due to its limitation in handling big data, Parallel Support Vector Machine is adapted for big data analysis.
Keywords: Big data, cloud storage, healthcare data, cardio vascular disease, classification algorithm, parallel SVM.
Graphical Abstract
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