A Survey on Risk Assessments of Heart Attack Using Data Mining Approaches - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue International Journal of Information Engineering and Electronic Business Année : 2019

A Survey on Risk Assessments of Heart Attack Using Data Mining Approaches

Résumé

This document presents the required layout of articles to Medical data mining has become one of the prominent issues in the field of data mining due to the delicate lifestyle opted by the people which are leading them towards various chronicle health diseases. Heart disease is one of the conspicuous public health concern worldwide issues. Since clinical data is growing rapidly owing to deficient health awareness, various techniques and scientific methods are opted for analyzing this huge data. Several data mining techniques such as Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Decision tree, Naïve Bayes and Artificial Neural Network (ANN) are introduced for the prediction of health disease. These techniques help to mine the relevant and useful amount of data, form the medical dataset which helps to provide beneficial information to the medical institutions. This study presents various issues related to healthcare and various machines learning algorithms which have to withstand to provide the best possible output. A comprehensive review of the literature has been summarized to put lights on the previous work done in this field.
Fichier principal
Vignette du fichier
IJIEEB-V11-N4-5.pdf (550.8 Ko) Télécharger le fichier
Origine Fichiers éditeurs autorisés sur une archive ouverte
Loading...

Dates et versions

hal-02188879 , version 1 (18-07-2019)

Identifiants

Citer

Yogita Solanki, Sanjiv Sharma. A Survey on Risk Assessments of Heart Attack Using Data Mining Approaches. International Journal of Information Engineering and Electronic Business, 2019, 11 (4), pp.43-51. ⟨10.5815/ijieeb.2019.04.05⟩. ⟨hal-02188879⟩
260 Consultations
307 Téléchargements

Altmetric

Partager

Gmail Mastodon Facebook X LinkedIn More