Prediction of Cardiovascular Disease on Self-Augmented Datasets of Heart Patients Using Multiple Machine Learning Models

Table 2

Prediction of cardiovascular attacks.

Reference	Gender based	Dataset	Feature selection techniques	Classification models	Accuracy	Optimization
Khan et al. [37]	No	A synthetic dataset across minority data space	No technique	Support machine vector	83.65% for RBF and 84.56% for linear	No optimization technique
Chen et al. [14]	No	17 left ventricle defective patients	No technique	Machine learning basic models	79% on an average	No optimization technique
Mehta et al. [16]	No	Self-created data	No technique	Machine learning basic models	79% on an average	No optimization technique
Ahmad et al. [4]	No	Self-created data	No technique	Machine learning basic models	79% on an average	No optimization technique
Zahid et al. [8]	No	Self-created data	No technique	Support machine vector	72%	No optimization technique
Chicco and Jurman [6]	No	Self-created data	No technique	Support machine vector	76%	No optimization technique