On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
A hypertext knowledge based for primary care - LIMEDS in LINCKS
SIGIR '89 Proceedings of the 12th annual international ACM SIGIR conference on Research and development in information retrieval
Future directions in knowledge-based systems
ACM Computing Surveys (CSUR) - Special issue: position statements on strategic directions in computing research
Processing unexact information in a medical used multiparadigm system
SAC '95 Proceedings of the 1995 ACM symposium on Applied computing
ELECTRE: A language using control structure expressions to specify synchronization
ACM '85 Proceedings of the 1985 ACM annual conference on The range of computing : mid-80's perspective: mid-80's perspective
Towards More Optimal Medical Diagnosing with Evolutionary Algorithms
Journal of Medical Systems
Intelligent systems: architectures and perspectives
Recent advances in intelligent paradigms and applications
Soft Computing for diagnostics in equipment service
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
A fuzzy expert system design for diagnosis of prostate cancer
CompSysTech '03 Proceedings of the 4th international conference conference on Computer systems and technologies: e-Learning
Expert Systems: Principles and Programming
Expert Systems: Principles and Programming
Fuzzy multi-criteria selection of object-oriented simulation software for production system analysis
Computers and Operations Research
A framework for application of neuro-case-rule base hybridization in medical diagnosis
Applied Soft Computing
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The task of medical diagnosis is a complex one, considering the level vagueness and uncertainty management, especially when the disease has multiple symptoms. A number of researchers have utilized the fuzzy-analytic hierarchy process (fuzzy-AHP) methodology in handling imprecise data in medical diagnosis and therapy. The fuzzy logic is able to handle vagueness and unstructuredness in decision making, while the AHP has the ability to carry out pairwise comparison of decision elements in order to determine their importance in the decision process. This study attempts to do a case comparison of the fuzzy and AHP methods in the development of medical diagnosis system, which involves basic symptoms elicitation and analysis. The results of the study indicate a non-statistically significant relative superiority of the fuzzy technology over the AHP technology. Data collected from 30 malaria patients were used to diagnose using AHP and fuzzy logic independent of one another. The results were compared and found to covary strongly. It was also discovered from the results of fuzzy logic diagnosis covary a little bit more strongly to the conventional diagnosis results than that of AHP.