A novel hybrid method based on fuzzy cognitive maps and fuzzy clustering algorithms for grading celiac disease

Prediction of stroke probability occurrence based on fuzzy cognitive maps

“…There are several methods for converting fuzzy linguistic variables because using triangular and trapezoidal membership functions in the medical context is more common than other membership functions [5,[11][12]. The present study used triangular and trapezoidal membership functions, such that the membership functions of the output concept of risk rate is shown in Figure 2.…”

“…The advantage of this method is that neurologists do not use numerical values to define causal relationships among concepts, but qualitatively describe the causality degree among the concepts. The fuzzy rule is evaluated for each interconnection using the fuzzy inference and the inferred fuzzy weight is calculated using the centre of area defuzzification methodology and the FCM initial weight matrix is obtained [3,12]. The following example is presented to illustrate how the numerical values of the weights proposed by the neurologists are obtained:…”

“…If the termination conditions are not met after 1000 iterations, specialists are asked to re-design a new FCM, and then the steps above are repeated for the new weight matrix and the reconstructed FCM model [12,[17][18].…”

“…There have been many studies in medicine over the past years using the fuzzy cognitive map and nonlinear Hebbian learning algorithm method. These studies have included the classification of the autism disorder [9], modelling the Parkinson's disease [10], classification of breast lesions [5,11], and Grading celiac disease [12]. In a previous study [9], the onset of childhood autism was predicted with regard to 23 major factors of the disease, such as enjoy being swung, take an interest in other children, and climbing on things.…”

“…In this study, the accuracy of UDH classification was determined to be 88% and 86% for ADH and DCIS, respectively, UDH was considered as a benign lesion, and ADH and DCIS were considered as malignant lesions. And in another research [12], celiac disease was graded as A, B 1 and B 2 among 89 cases considering 7 major determinant factors of the disease using FCM and Possibilistic Fuzzy C-Means (PFCM) clustering algorithm. NHL algorithm was used to increase functionality and accuracy of FCM classification.…”