  Low Back Pain (LBP) is a common medical condition that deprives many
individuals worldwide of their normal routine activities. In the absence of
external biomarkers, diagnosis of LBP is quite challenging. It requires dealing
with 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 representation
scheme for handling imprecision in knowledge, offering a suitable design
methodology for a fuzzy knowledge base and a fuzzy inference system. The fuzzy
knowledge base is constructed in modular fashion, with each module capturing
interrelated medical knowledge about the relevant clinical history, clinical
examinations and laboratory investigation results. This approach in design
ensures optimality, consistency and preciseness in the knowledge base and
scalability. The fuzzy inference system, which uses the Mamdani method, adopts
the triangular membership function for fuzzification and the Centroid of Area
technique for defuzzification. A prototype of this system has been built using
the knowledge extracted from the domain expert physicians. The inference of the
system against a few available patient records at the ESI Hospital, Sealdah has
been checked. It was found to be acceptable by the verifying medical experts.
