Inproceedings,
Genetic Programming for the Generation of Crisp and Fuzzy Rule Bases in Classification and Diagnosis of Medical Data
First International NAISO Congress on Neuro Fuzzy Technologies, Havana, Cuba, (16-19 January 2002)
Abstract
This paper demonstrates two methodologies for the
construction of rule-based systems in medical decision
making. The first approach consists of a method
combining genetic programming and heuristic
hierarchical rule-base construction. The second model
is composed by a strongly-typed genetic programming
system for the generation of fuzzy rule-based systems.
Two different medical domains are used to evaluate the
models. The first field is the diagnosis of subtypes of
Aphasia. Two models for crisp rule-bases are presented.
The first one discriminates between four major types
and the second attempts the classification between all
common types. A third model consisted of a GPgenerated
fuzzy rule-based system is tested on the same domain.
The second medical domain is the classification of
Pap-Smear Test examinations where a crisp rulebased
system is constructed. Results denote the effectiveness
of the proposed systems. Comparisons on the system's
comprehensibility and the transparency are included.
These comparisons include for the Aphasia domain,
previous work consisted of two neural network models.
