Knowledge-driven Intuitionistic Fuzzy Decision Support for finding out the causes of Obesity

Abstract— In this paper, we propose an Intuitionistic Fuzzy decision support system for determining the causes of a more or less common disorder – obesity. Obesity can be simply lifestyle related i.e. excessive food energy intake and a lack of physical activity related or it may be caused due to hormonal, pathological or genetic factors. Whenever a patient is examined, our goal is to find out the cause of obesity so that appropriate treatment can be prescribed to the patient. All this involves a particular amount of uncertainty and imprecision. We take the help of an intuitionistic fuzzy diagnostic system that works at two levels. At the first level, we try to filter out the set of patients, who don’t exhibit the signs and symptoms of hormonal, pathological or genetic disorders i.e. reduced set of patients (suffering from SIMPLE OBESITY). At the second level, we diagnose the rest of the obese patients for Metabolic or Cushing’s syndrome (only two disorders have been taken for the sake of convenience). The values used in the databases are both crisp and intuitionistic fuzzy in nature. The latter ones may be directly recorded or may get their values quantized from linguistic expressions such as MILD, MODERATE, LOW.