Title :
Predictions in heart disease using techniques of data mining
Author :
Gandhi, Monika ; Singh, Shailendra Narayan
Author_Institution :
Comput. Sci. & Eng. Dept., Amity Univ., Noida, India
Abstract :
As huge amount of information is produced in medical associations (healing facilities, therapeutic focuses) yet this information is not properly utilized. The health care system is "data rich" however "knowledge poor ". There is an absence of successful analysis methods to find connections and patterns in health care data. Data mining methods can help as remedy in this circumstance. For this reason, different data mining techniques can be utilized. The paper intends to give details about various techniques of knowledge abstraction by using data mining methods that are being used in today\´s research for prediction of heart disease. In this paper, data mining methods namely, Naive Bayes, Neural network, Decision tree algorithm are analyzed on medical data sets using algorithms.
Keywords :
Bayes methods; data mining; decision trees; diseases; medical computing; neural nets; data mining techniques; decision tree algorithm; health care system; heart disease prediction; knowledge abstraction; medical data sets; naive Bayes; neural network; Biological neural networks; Data mining; Decision trees; Diseases; Heart; Medical diagnostic imaging; Data mining; Decision tree; Heart disease; Naïve Bayes; Neural network; classification; prediction;
Conference_Titel :
Futuristic Trends on Computational Analysis and Knowledge Management (ABLAZE), 2015 International Conference on
Conference_Location :
Noida
Print_ISBN :
978-1-4799-8432-9
DOI :
10.1109/ABLAZE.2015.7154917