TRAINING ANFIS SYSTEM WITH GENETIC ALGORITHM FOR DIAGNOSIS OF PROSTATE CANCER

Year 2018, Volume: 13 Issue: 4, 301 - 309, 13.10.2018

Mustafa Turan Arslan , Derya Arslan Bülent Haznedar

Abstract

Prostate cancer is one of
the most common types of cancer among males as well as causing the most deaths.
Early diagnosis of prostate cancer plays an important role in the treatment of
the disease. Therefore, microarray technology is widely used in the diagnosis
of inherited diseases such as prostate cancer. With this technology, it is
possible to obtain more knowledge about cancer by analyzing thousands of gene
expressions. However, it is quite difficult to analyze complex relationships
among thousands of genes in microarray data. For this reason, high performance
artificial intelligence-based classification methods are needed in recent
years. In this study, a hybrid method has been proposed for optimizing the
parameters of Adaptive Neuro Fuzzy Inference System (ANFIS) with Genetic
Algorithm (GA) in order to classify prostate cancer gene expression profiles.
The performance of the proposed method is compared with those of ANFIS models
trained by different learning algorithms. According to obtained results, the
proposed method is more successful than the other methods, with the accuracy of
90.32%.

Keywords

ANFIS, Microarray, Prostate cancer, Classification, Genetic Algorithm

TRAINING ANFIS SYSTEM WITH GENETIC ALGORITHM FOR DIAGNOSIS OF PROSTATE CANCER

Abstract

Prostate cancer is one of the most common types of cancer among males as well as causing the most deaths. Early diagnosis of prostate cancer plays an important role in the treatment of the disease. Therefore, microarray technology is widely used in the diagnosis of inherited diseases such as prostate cancer. With this technology, it is possible to obtain more knowledge about cancer by analyzing thousands of gene expressions. However, it is quite difficult to analyze complex relationships among thousands of genes in microarray data. For this reason, high performance artificial intelligence-based classification methods are needed in recent years. In this study, a hybrid method has been proposed for optimizing the parameters of Adaptive Neuro Fuzzy Inference System (ANFIS) with Genetic Algorithm (GA) in order to classify prostate cancer gene expression profiles. The performance of the proposed method is compared with those of ANFIS models trained by different learning algorithms. According to obtained results, the proposed method is more successful than the other methods, with the accuracy of 90.32%.

Keywords

Microarray, Prostate cancer, Classification, ANFIS, Genetic Algorithm

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