Open AccessAnalysis Of Single And Hybrid Data Mining Techniques For Prediction Of Heart Disease Using Real Time Dataset
Author(s) -
Syed Ahmed Yasin,
P.V.R.D.Prasad Rao
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.32.13536
Subject(s) - data mining , computer science , identification (biology) , disease , heart disease , data set , medical prescription , data extraction , process (computing) , data science , set (abstract data type) , artificial intelligence , medicine , medline , botany , political science , law , pharmacology , biology , programming language , operating system
Data mining and healthcare has strong relations as data mining is a process where we can analyze enormous set of data and after extraction meaning of data can be understood. As medical data is in bulk which leads to the need of data analytics tool for extraction of useful information or knowledge .Disease Prediction is one of the applications where many researchers are working so that they can answer whether to apply single or compound data mining technique. Heart related disease is the major cause of deaths in past decades. Use of single technique in treatment of heart disease is showing variable accuracy. Current leading research study is all about to check the effect of compound data mining technique will show enhanced results in the prognosis of heart related disease or not, but the major issue arises of identification a suitable treatment for heart disease patient. This survey paper notify gap in research findings on heart disease prognosis and prescription data and proposes a model which will fill the gap and shows enhanced accuracy.