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Low Back Pain (LBP) is a common medical condition that deprives manyindividuals worldwide of their normal routine activities. In the absence ofexternal biomarkers, diagnosis of LBP is quite challenging. It requires dealingwith several clinical variables, which have no precisely quantified values.Aiming at the development of a fuzzy medical expert system for LBP management,this research proposes an attractive lattice-based knowledge representationscheme for handling imprecision in knowledge, offering a suitable designmethodology for a fuzzy knowledge base and a fuzzy inference system. The fuzzyknowledge base is constructed in modular fashion, with each module capturinginterrelated medical knowledge about the relevant clinical history, clinicalexaminations and laboratory investigation results. This approach in designensures optimality, consistency and preciseness in the knowledge base andscalability. The fuzzy inference system, which uses the Mamdani method, adoptsthe triangular membership function for fuzzification and the Centroid of Areatechnique for defuzzification. A prototype of this system has been built usingthe knowledge extracted from the domain expert physicians. The inference of thesystem against a few available patient records at the ESI Hospital, Sealdah hasbeen checked. It was found to be acceptable by the verifying medical experts.

Lattice-Based Fuzzy Medical Expert System for Low Back Pain Management