This project is aimed at creating a machine learning model which can predict cardiovascular disease using various parameters including history of Covid-19. Standard tools will be used which are easily available to all, and with some modifications, they can accurately predict cardiovascular disease. The objective is to predict early onset heart disease in patients during a treatment procedure which can allow medical professionals to save more lives using the power of machine learning. I propose a system that integrates various machine learning algorithms for the purpose of achieving better heart disease prediction accuracy and issuing better diagnostics.
Data gathering and the selection of key attributes are the first steps in the system's operation. The necessary data is then pre-processed into the necessary format. The dataset is then split into training data and testing data. Using the training set, the algorithms are used to train the model. The system is tested using test data in order to determine its accuracy. The following modules are used to implement this system.
- Data collection
- Feature selection
- Data Pre-processing
- Data balancing
- Creation of Model