Classification models for heart disease prediction using feature selection and PCA

Anna Karen Gárate-Escamilla; Amir Hajjam El Hassani; Emmanuel Andrès

doi:10.1016/j.imu.2020.100330

ScienceGate Book Chapters

JOURNAL ARTICLE

Classification models for heart disease prediction using feature selection and PCA

Anna Karen Gárate-Escamilla Amir Hajjam El Hassani Emmanuel Andrès

Year: 2020 Journal: Informatics in Medicine Unlocked Vol: 19 Pages: 100330-100330 Publisher: Elsevier BV

DOI: 10.1016/j.imu.2020.100330

Get Full-Text PDF Get Analytical Report

Keywords:

Principal component analysis Random forest Feature selection Artificial intelligence Dimensionality reduction Pattern recognition (psychology) Machine learning Feature (linguistics) Relevance (law) Computer science Heart disease Curse of dimensionality Medicine Cardiology

Metrics

405

Cited By

94.18

FWCI (Field Weighted Citation Impact)

Refs

1.00

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Artificial Intelligence in Healthcare

Health Sciences → Health Professions → Health Information Management

ECG Monitoring and Analysis

Health Sciences → Medicine → Cardiology and Cardiovascular Medicine

Classification models for heart disease prediction using feature selection and PCA

Metrics

Citation History

Topics

Related Documents

Classification models combined with Boruta feature selection for heart disease prediction

Comparative Analysis of Multiclass Heart Disease Prediction Classification Models using Preprocessing and Feature Selection

Heart Disease Prediction Using Classification Models

Classification model for heart disease prediction using correlation and feature selection techniques

Improving Heart Disease Prediction Using Feature Selection Approaches