Development of Severity Index for Oral Epithelial Dysplasia Using Fuzzy Group Decision Making Algorithm

BackgroundOral epithelial dysplasia (OED) grading suffers from several levels of uncertainties and imprecision. An index is preferred in this context to improve reliability and reduce subjectivity in diagnostic decision making. In this study, a fuzzy logic-based disease severity index (SI) is formulated considering standard histopathological features used in OED grading. MethodsOral onco-pathologists were asked to independently provide weights of different features, according to their clinical significance in the context of dysplasia. Aggregated weight of each feature was calculated from individual assessment of different onco-pathologists by a fuzzy logic-based group decision making algorithm. Confidence levels of experts were also included to improve robustness of the method. SI was generated by integrating abnormality score of each feature with its weight. Abnormality degree of each feature was expressed in linguistic terms by onco-pathologists which were subsequently represented by a triangular fuzzy number. Fuzzy membership function was used as it can capture the ambiguity of experts opinion regarding abnormality of individual feature. Finally, defuzzification was used to get a crisp index from weighted sum of all features. ResultSI was found to be statistically different (p View larger version (36K): org.highwire.dtl.DTLVardef@5a5e28org.highwire.dtl.DTLVardef@dba3a9org.highwire.dtl.DTLVardef@1d5cc7corg.highwire.dtl.DTLVardef@16404b5_HPS_FORMAT_FIGEXP M_FIG Graphical abstract C_FIG