Download Using Data Mining Techniques In Heart Disease Diagnosis And

Using Data Mining Techniques In Heart Disease Diagnosis
And Treatment
Abstract:
Disease diagnosis is one of the applications where data mining tools are proving successful
results. Heart disease is the leading cause of death all over the world. Using Single Data Mining
Technique in the diagnosis of heart disease has been comprehensively investigated showing
acceptable levels of accuracy. However, using data mining techniques to identify a suitable
treatment for heart disease patients has received less attention. This paper identifies gaps in there
search on heart disease diagnosis and treatment and proposes a model to systematically close
those gaps to discover if applying data mining techniques to heart disease treatment data can
provide as reliable performance as that achieved india gnosing heart disease.
Existing System:
In Existing system, the single data mining technique is used to diagnose the heart disease. There
is no previous research that identifies which data mining technique can provide more reliable
accuracy in identifying suitable treatment for heart disease patients.
Practical use of healthcare database systems and knowledge discovery is difficult in heart disease
diagnosis.
Disadvantages:
Hospitals do not provide the same quality of service even though they provide the same type of
service.
There is no previous research that identifies which data mining technique can provide more
reliable accuracy in identifying suitable treatment for heart disease patients.
It takes more time consumption for practical use of healthcare database systems.
Further Details Contact: A Vinay 9030333433, 08772261612
Email: [email protected] | www.takeoffprojects.com
Proposed System:
In Proposed System, we are applying data mining techniques (Hybrid) in identifying suitable
treatments for heart disease patients.
Apply single data mining techniques to heart disease diagnosis benchmark dataset to establish
baseline accuracy for each single data mining technique in the diagnosis of heart disease patients.
Apply the same single data mining techniques used in heart disease diagnosis to heart disease
treatment dataset to investigate if single data mining techniques can achieve equivalent (or
better) results in identifying suitable treatments as that achieved in the diagnosis.
Apply hybrid data mining techniques to heart disease diagnosis benchmark dataset to establish
baseline accuracy for each hybrid data mining technique in the diagnosis of heart disease
patients.
Apply the same hybrid data mining techniques used in heart disease diagnosis to heart disease
treatment dataset to investigate if hybrid data mining techniques can achieve equivalent (or
better) results in identifying suitable treatments as that achieved in the diagnosis.
Advantages:
By applying data mining techniques to help health care professionals in the diagnosis of heart
disease.
Hybrid data mining techniques are used for selecting the suitable treatment for heart disease
patients.
High Performance and Accuracy.ALGORITHM USED: 1. Navie BayesTime consumption is
less.
Further Details Contact: A Vinay 9030333433, 08772261612
Email: [email protected] | www.takeoffprojects.com
High Performance and Accuracy.ALGORITHM USED: 1. Navie Bayes 2. Decision Tree 3.
Neural Networks 4. Association Rule 5. RegressionARCHITECTURE DIAGRAM:Time
consumption is less.
System Requirements:
Hardware Requirements:
• Intel Pentium IV
• 256/512 MB RAM
• 1 GB Free disk space or greater
• 1 GB on Boot Drive
• 17” XVGA display monitor
• 1 Network Interface Card (NIC)
Software Requirements:
• MS Windows XP/ Windows 7
• MS IE Browser 6.0/later
•JAVA
Further Details Contact: A Vinay 9030333433, 08772261612
Email: [email protected] | www.takeoffprojects.com