• YADVINDER SINGH
• RAMAN GOYAL

Present day medical diagnosis requires various kinds of factors understanding and x-ray analysis which can be considered as base to give the final diagnoses. Whenever a diagnosis is given, different factors has to be deeply understood and be compared depending on different situations and factor combinations to place the final verdict. Due to the different levels of concentrations or strengths of the various factor, there is a probability of getting best as well as worst combinations. The factors need to be analysed with their concentration values according to different case, and is one of the most tedious task. In this paper, fuzzy set theory is incorporated to handle uncertainties. The fuzzy logic provides a mathematical framework for representation and processing of expert knowledge. The concept of if-then rules plays a role in approximation of the variables like cross over point. The proposed technique is able to improve the decision-making power of the diagnosis prediction. This algorithm converts various factors to fuzzy data and fuzzy data into de-fuzzification.

Fuzzy inference system (FIS), Insulin-dependent diabetes mellitus (IDDM), Non-insulin-dependent diabetes mellitus (NIDDM), Interval Type-2 Neuro-Fuzzy Inference System (IT2FIS), Quality of Service (QoS)

"A Novel Approach to Diagnosis of Diabetes with Prevalent Factor Concentration", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 1, page no.540-544, January-2018, Available :http://www.jetir.org/papers/JETIR1801103.pdf

"A Novel Approach to Diagnosis of Diabetes with Prevalent Factor Concentration", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 1, page no. pp540-544, January-2018, Available at : http://www.jetir.org/papers/JETIR1801103.pdf