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رایانش نرم و فناوری اطلاعات، جلد ۵، شماره ۱، صفحات ۴۵-۰
عنوان فارسی A Hybrid Fuzzy-GA Approach Applied to An Expert System for Diagnosis of Liver Tumor
چکیده فارسی مقاله Applications of soft computing techniques have been concentrated for management of the uncertainty associated to the medical diagnosis in the recent decade. This article presents a Fuzzy Expert System (FES) for diagnose of metastasis in the liver which is one of the most common malignant hepatic tumors. Furthermore, the proposed FES has been optimized using a genetic algorithm. The purpose of the hybrid fuzzy-GA approach is to adjust the FES parameters to enhance the system accuracy while the system interpretability has been kept. To experiment the proficiency of the intelligent Fuzzy-GA model, the performance of the system was evaluated with real dataset of patients gathered from the Noor Medical Imaging Center in Tehran. The FES performance was compared to the diagnosis of specialists before and after optimization with the GA. The results demonstrate that this system has a high capability in the management of uncertainty in the diagnosis with a high accuracy. The hybrid fuzzy-GA approach for hepatic tumors diagnosis is promising to assistant the specialists for early diagnosis of the cancer and saving more lives. 
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عنوان انگلیسی A Hybrid Fuzzy-GA Approach Applied to An Expert System for Diagnosis of Liver Tumor
چکیده انگلیسی مقاله Applications of soft computing techniques have been concentrated for management of the uncertainty associated to the medical diagnosis in the recent decade. This article presents a Fuzzy Expert System (FES) for diagnose of metastasis in the liver which is one of the most common malignant hepatic tumors. Furthermore, the proposed FES has been optimized using a genetic algorithm. The purpose of the hybrid fuzzy-GA approach is to adjust the FES parameters to enhance the system accuracy while the system interpretability has been kept. To experiment the proficiency of the intelligent Fuzzy-GA model, the performance of the system was evaluated with real dataset of patients gathered from the Noor Medical Imaging Center in Tehran. The FES performance was compared to the diagnosis of specialists before and after optimization with the GA. The results demonstrate that this system has a high capability in the management of uncertainty in the diagnosis with a high accuracy. The hybrid fuzzy-GA approach for hepatic tumors diagnosis is promising to assistant the specialists for early diagnosis of the cancer and saving more lives. 
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نویسندگان مقاله بنفشه امیرحسینی | banafsheh amirhosseini
department of artificial intelligence, shahr-e-qods branch, islamic azad university, tehran, iran

سازمان اصلی تایید شده: دانشگاه آزاد اسلامی علوم و تحقیقات (Islamic azad university science and research branch)

راحیل حسینی | rahil hosseini
department of artificial intelligence, shahr-e-qods branch, islamic azad university, tehran, iran

سازمان اصلی تایید شده: دانشگاه آزاد اسلامی علوم و تحقیقات (Islamic azad university science and research branch)

مهدی مزینانی | mahdi mazinani
department of electronic engineering, shahr-e-qods branch, islamic azad university, tehran, iran

سازمان اصلی تایید شده: دانشگاه آزاد اسلامی علوم و تحقیقات (Islamic azad university science and research branch)

نشانی اینترنتی http://jscit.nit.ac.ir/index.php/jscit/article/view/Vol.5_No.1_5
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