M.A.Saleem Durai and N.Ch.S.N.Iyengar (2010) EFFECTIVE ANALYSIS AND DIAGNOSIS OF LUNG CANCER USING FUZZY RULES

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EFFECTIVE ANALYSIS AND DIAGNOSIS OF LUNG CANCER USING FUZZY RULES

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CONTRIBUTORS:

	Author:	M.A.Saleem Durai
	Author:	N.Ch.S.N.Iyengar

JOURNAL:

International Journal of Engineering Science and Technology (IJEST), 2(6), 2102 - 2108.

YEAR:

2010

PUB TYPE:

Journal Article

SUBJECT(S):

Lung Diseases, Diagnostic System, Fuzzy Rule Base, Threshold Value and Membership Value.

DISCIPLINE:

Engineering and Applied Sciences

HTTP:

http://www.ijest.info/docs/IJEST10-02-06-99.pdf

LANGUAGE:

English

PUB ID:

103-489-819 (Last edited on 2011/06/24 22:51:32 GMT-6)

SPONSOR(S):

ABSTRACT:
In this paper, the structure of a lung cancer analysis system is presented. The main focus for the development of the system is on the architecture and the algorithm used to find the probable disease, stage and the appropriate treatment of cancer a patient may have. The disease is determined by using a rule base, populated by rules made for different types of lung cancer. The algorithm uses the output of the rule base (i.e. the disease name) and the symptoms entered by the user to determine the stage of cancer the patient is in. Both these results (disease name and stage) help the diagnostic logic to determine the treatment for the patient with accuracy. Our diagnosis does a complex analysis of all the information gathered about our symptoms. In this paper, we have evolved a method of choosing the best treatment for cancer using fuzzy decision making techniques.

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