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Disease diagnosis is very important for the treatment of the disease. Therefore a more accurate diagnosis mechanism is required that can accurately diagnose the disease in its early stage. This study aims to develop a diabetes diagnosis mechanism that can accurately predict whether a person is diabetic or not based on the given input data of patients. Two expert systems have been proposed. One is Fuzzy Logic Based Diabetes Diagnosis System (FLDDS) which is based on the fuzzy logic and other one is Vague Diabetes Diagnosis System (VDDS) which is based on the concept of vague logic.

Produktbeschreibung
Disease diagnosis is very important for the treatment of the disease. Therefore a more accurate diagnosis mechanism is required that can accurately diagnose the disease in its early stage. This study aims to develop a diabetes diagnosis mechanism that can accurately predict whether a person is diabetic or not based on the given input data of patients. Two expert systems have been proposed. One is Fuzzy Logic Based Diabetes Diagnosis System (FLDDS) which is based on the fuzzy logic and other one is Vague Diabetes Diagnosis System (VDDS) which is based on the concept of vague logic.
Autorenporträt
Dr Supriya Raheja, is currently working as a Senior Assistant Professor, NCU. She has more than 10 years of extensive teaching experience. She is a committed researcher in the field of Operating system and vague set theory. She has published more than 25 papers in peer reviewed reputed International Journals and in International Conferences.