جستجوی مقالات مرتبط با کلیدواژه "استخراج ویژگی و انتخاب ویژگی" در نشریات گروه "فناوری اطلاعات"

Breast cancer is one of the most common causes of death among women around the world, but early and accurate diagnosis of this type of cancer can dramatically improve treatment. Thermal imaging is one of the primary methods of diagnosing breast cancer. The computer diagnosis system can also be used to help physicians to increase the accuracy of interpretation of results. This paper presents an intelligent computer diagnostic system for the detection of breast cancer using thermal imaging. The proposed intelligent computer diagnosis system includes SFTA method for feature extraction and SVM, kNN and D-Tree algorithms for classification of results. The performance of the proposed intelligent computer diagnosis system is evaluated using the DMR-IR and Fluminense Federal University databases and MATLAB2018, when using the cuckoo feature selection algorithm and without using the feature selection algorithm. The results show that the average accuracy, sensitivity and specificity are 99%, 99.5% and 98.03%, respectively, using the cuckoo feature selection algorithm and SVM classification algorithm. Also, the presented computer diagnostic system has advantages compared to other computer diagnosis systems. These results indicate that the use of SFTA feature extraction method, cuckoo feature selection algorithm, SVM classification algorithm and DMR-IR database in the proposed computer diagnosis system can improve the evaluation results.