Fuzzy Expert System for Decision Making in Myocardial Infarction

• Main Author: A. Raof, Rafikha Aliana
• Format: Thesis
• Language: English; English
• Published: 2003
• Subjects: QA76.76 Fuzzy System.
• Online Access: http://etd.uum.edu.my/1103/1/RAFIKHA_ALIANA_BT._A._RAOF.pdf; http://etd.uum.edu.my/1103/2/1.RAFIKHA_ALIANA_BT._A._RAOF.pdf; http://etd.uum.edu.my/1103/
• Institution: Universiti Utara Malaysia

Decision support system has been introduced in many domains and currently the computering world is focusing on decision support system with knowledge-bused. Knowledge system is one of the branches in artificial intellengence (AI), which incorporates human knowledge into the system us a result of knowledge acquistion process. Hybrid AI system, which is composed of multiple AI methods, has shown quite remarkable results in diagnosis and so far only a few of such approach has been done in known us FEMInS. This system integrates fuzzy logic technology with expert system, which helps the general medical practitioner to predict as well as diagnosing heart attack based on early symptons. Since fuzzy logic can be used for prediction and expert system can provide explanations and reasoning the combination of both fields is suitable for medical domain system, which generally needs to cater the problems of uncertainty and provide the explanation of the results to the user. FEMInS development has demonstrated that fuzzy logic can handle uncertainty better than expert system. This is due to the fact that fuzzy logic uses multi label and multi confidence value to reach the conclusion.