Comparing the Performances of Neural Network and Rough Set Theory to Reflect the Improvement of Prognostic in Medical Data

• المؤلف الرئيسي: Nur Aniza, Alang Ismail
• التنسيق: أطروحة
• اللغة: English; English
• منشور في: 2009
• الموضوعات: QA76 Computer software
• الوصول للمادة أونلاين: http://etd.uum.edu.my/1909/1/Nur_Aniza_Bt_Alang_Ismail.pdf; http://etd.uum.edu.my/1909/2/1.Nur_Aniza_Bt_Alang_Ismail.pdf; http://etd.uum.edu.my/1909/

In this research, I investigate and compared two of Artificial Intelligence (AI)techniques which are; Neural network and Rough set will be the best technique to be use in analyzing data. Recently, AI is one of the techniques which still in development process that produced few of intelligent systems that helped human to support their daily life such as decision making. In Malaysia, it is newly introduced by a group of researchers from University Science Malaysia. They agreed with others world-wide researchers that AI is very helpful to replaced human intelligence and do many works that can be done by human especially in medical area.In this research, I have chosen three sets of medical data; Wisoncin Prognostic Breast cancer, Parkinson’s diseases and Hepatitis Prognostic. The reason why the medical data is selected for this research because of the popularity among the researchers that done their research in AI by using medical data and the prediction or target attributes is clearly understandable. The results and findings also discussed in this paper. How the experiment has been done; the steps involved also discussed in this paper. I also conclude this paper with conclusion and future work.