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Research Journal of Pharmacy and Technology
ISSN: 0974-360X(Online), 0974-3618(Print)
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List of Refereed Journals published by UGC, New Delhi on 28-03-2017-- AJRC (Sr. No.-1025); AJM (Sr. No.-2497); RJET (Sr. No.-7220); RJPP (Sr. No.- 7232): RJPPD (Sr. No.- 7234); RJPT (Sr. No.-7235)
List of Refereed Journals published by UGC, New Delhi on 11-01-2017-- Research Journal of Pharmacy and Technology (Sr. No.-275); Asian Journal of Management (Sr. No.-3986); Asian Journal of Research in Chemistry (Sr. No.-4008); Research Journal of Engineering and Technology (Sr. No.-31787); Research
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An Expert System to Deduce Knowledge on Cause for variant Diseases Using Mining Techniques
A. Pio Sajin
G. Hansie Shylu
Baron Sam B
A. Pio Sajin1, S. Devagladis2, G. Hansie Shylu2, Baron Sam B1
1Assistant Professor, Sathyabama University, Chennai.
2Student, Sathyabama University, Chennai.
A Disease is an abnormal condition or a disorder of a structure or function in a human that produces specific symptoms or affects their regular human lifestyle. Healthcare Industry which generates large amount of data those are too difficult to be analyzed by traditional method. Hence computer assisted methods are necessary to make correct decision. The main objective of this project is to develop a disease prediction system using data mining techniques like Apriorialgorithm; association mining. It explores a novel analytic method with clustering techniques under distributed system. The result which is obtained from this expert system will help us to be aware of the forthcoming diseases and that will help us to be aware and take preventive steps.
Association rules, Classification techniques, Apriori algorithm.
A. Pio Sajin, S. Devagladis, G. Hansie Shylu, Baron Sam B. An Expert System to Deduce Knowledge on Cause for variant Diseases Using Mining Techniques. Research J. Pharm. and Tech. 2017; 10(3): 857-860.
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