Classification and Categorization of Blood Infection Using Fuzzy Inference System
Harsh Khatter1, Anjali Jain2, Poonam Pandey3
1Mr. Harsh Khatter, Department of Computer Science, ABES Engineering College, Ghaziabad, India.
2Ms. Anjali Jain, IT Department, U.P Technical University, ABES Engineering Collge, Ghaziabad, India.
3Ms. Poonam Pandey, Department of Computer Science, ABES Engineering College, Ghaziabad, India.
Manuscript received on April 15, 2015. | Revised Manuscript received on April 26, 2015. | Manuscript published on March 05, 2015. | PP: 95-97| Volume-5, Issue-2, May 2015. | Retrieval Number: B2615055215/2015©BEIESPP
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Abstract: From last few decades the human body infections and diseases are growing in exponential manner. As per the medical report, in every three months a new infection or viral comes in existence with some new explode to effect the human race. To test whether the infection is in body or not, Blood tests are the common methods. Most of the diseases are beyond the doctor’s study or some recently spread virus infected the blood or human body. In such cases doctors use to give the treatment of other disease having same symptoms or same blood test cases. In this paper we are trying to make such a system which will spread awareness among doctors about the infections. The proposed system will work on the basis of fuzzy logic and neural network with the help of inference engine and its rules. The simulation will be done using Matlab. The proposed approach of using fuzzy logic and inferences with neural networks training in blood samples on real test cases of blood report is a novel idea.
Keywords: About four key words or phrases in alphabetical order, separated by commas.