Computational Intelligence for Medical Knowledge Acquisition with Application to Glaucoma

This paper presents an approach that integrates computational intelligence/soft computing paradigms with clinical investigation methods and knowledge. Computational intelligence methods (including fuzzy logic, neural networks and genetic algorithms) deal in a suitable way with imprecision, uncertainty and partial truth. These aspects can be found quite often in practical medical activities and in medical knowledge. The proposed approach uses a knowledge discovery process in order to develop an intelligent system for diagnosis and prediction of glaucoma. The knowledge acquired is embedded in a fuzzy logic inference system. The resulting Neuro-fuzzy Glaucoma Diagnosis and Prediction System is expected to lower the effort, difficulties and risk cost related to this disease (the leading cause of blindness in North America.) Key words: Computational intelligence, fuzzy logic, knowledge discovery, glaucoma, risk evaluation, prediction

• Type: Conference
• Year: 2002
• Where: IEEEICCI
• Authors: Nicolae Varachiu, Cynthia Karanicolas, Mihaela Ulieru
• Keywords: Artificial Intelligence, Computational Intelligence, Fuzzy Logic, IEEEICCI 2002, Knowledge Discovery