Fuzzy Expert System for Decision Making in Myocardial Infarction
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 kn...
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2003
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| Online Access: | https://etd.uum.edu.my/1103/1/RAFIKHA_ALIANA_BT._A._RAOF.pdf https://etd.uum.edu.my/1103/2/1.RAFIKHA_ALIANA_BT._A._RAOF.pdf |
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my-uum-etd.11032013-07-24T12:10:25Z Fuzzy Expert System for Decision Making in Myocardial Infarction 2003-08-08 A. Raof, Rafikha Aliana Sekolah Siswazah Graduate School QA76.76 Fuzzy System. 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. 2003-08 Thesis https://etd.uum.edu.my/1103/ https://etd.uum.edu.my/1103/1/RAFIKHA_ALIANA_BT._A._RAOF.pdf application/pdf eng validuser https://etd.uum.edu.my/1103/2/1.RAFIKHA_ALIANA_BT._A._RAOF.pdf application/pdf eng public masters masters Universiti Utara Malaysia |
| institution |
Universiti Utara Malaysia |
| collection |
UUM ETD |
| language |
eng eng |
| topic |
QA76.76 Fuzzy System. |
| spellingShingle |
QA76.76 Fuzzy System. A. Raof, Rafikha Aliana Fuzzy Expert System for Decision Making in Myocardial Infarction |
| description |
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. |
| format |
Thesis |
| qualification_name |
masters |
| qualification_level |
Master's degree |
| author |
A. Raof, Rafikha Aliana |
| author_facet |
A. Raof, Rafikha Aliana |
| author_sort |
A. Raof, Rafikha Aliana |
| title |
Fuzzy Expert System for Decision Making in Myocardial Infarction |
| title_short |
Fuzzy Expert System for Decision Making in Myocardial Infarction |
| title_full |
Fuzzy Expert System for Decision Making in Myocardial Infarction |
| title_fullStr |
Fuzzy Expert System for Decision Making in Myocardial Infarction |
| title_full_unstemmed |
Fuzzy Expert System for Decision Making in Myocardial Infarction |
| title_sort |
fuzzy expert system for decision making in myocardial infarction |
| granting_institution |
Universiti Utara Malaysia |
| granting_department |
Sekolah Siswazah |
| publishDate |
2003 |
| url |
https://etd.uum.edu.my/1103/1/RAFIKHA_ALIANA_BT._A._RAOF.pdf https://etd.uum.edu.my/1103/2/1.RAFIKHA_ALIANA_BT._A._RAOF.pdf |
| _version_ |
1747827071703318528 |