A novel approach for the effective prediction of cardiovascular disease using applied artificial intelligence techniques.

ABSTRACT:

Aims

The objective of this research is to develop an effective cardiovascular disease prediction framework using machine learning techniques and to achieve high accuracy for the prediction of cardiovascular disease.

Methods

In this paper, we have utilized machine learning algorithms to predict cardiovascular disease on the basis of symptoms such as chest pain, age and blood pressure. This study incorporated five distinct datasets: Heart UCI, Stroke, Heart Statlog, Framingham and Coronary Heart dataset obtained from online sources. For the implementation of the framework, RapidMiner tool was used. The three-step approach includes pre-processing of the dataset, applying feature selection method on pre-processed dataset and then applying classification methods for prediction of

SUBMITTER: Mir A 

PROVIDER: S-EPMC11631242 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature