Early Detection of Heart Disease Using Quantum Computing and Partitioned Random Forest Methods

The authors propose a hybrid quantum random forest (HQRF) algorithm that combines quantum neural networks and random forest methods to efficiently predict heart disease with high accuracy, while considering the effects of outliers in the dataset.