Machine Learning-Based Detection of Cardiovascular Disease using Classification and Feature Selection
Anuj Kumar Jain, Kamal Kumar, Raj Gaurang Tiwari, Nitin B. Jain, Vinay Gautam, Naresh Kumar Trivedi
Abstract
The application of ameliorative datasets to foretell chronic diseases has grasped considerable attention amongst data scientists all around the globe. The study is based on the Cardiovascular disease dataset. Cardiovascular disease is a broad term concerning disorders of the heart and blood vessels and is ranked to be the topmost cause of demise worldwide. Various feature selection techniques have been applied to each of the given classification algorithms and the features which give the best accuracy are then utilized for that particular algorithm.
Topics & Concepts
Feature selectionComputer scienceArtificial intelligenceDiseaseSelection (genetic algorithm)Feature (linguistics)Machine learningDemiseStatistical classificationFeature extractionPattern recognition (psychology)Data miningMedicinePathologyPhilosophyLinguisticsLawPolitical scienceArtificial Intelligence in HealthcareImbalanced Data Classification TechniquesECG Monitoring and Analysis