The healthcare industries have a reservation of huge size of cardiovascular data, which can be mined in order to discover arcane information for making an effective decision of heart disease detection. In this study, a tentative design of a cloud-based heart disease prediction system has been proposed in the Android platform to detect impending heart disease. For the most accurate detection of the heart disease, an efficient machine learning technique can be used which has been derived from a distinctive analysis among several machine learning algorithms.
The most efficient algorithm can be applied to the cloud-based server. This algorithm deals with a large size of the dataset, where 10-fold cross-validation is applied in order to analyze the performance of heart disease detection and 97.53% accuracy has been calculated from the SVM algorithm.