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Application of a New Hybrid Machine Learning (Fuzzy-PSO) for Detection of Breast’s Tumor

Hamzeh GhorbaniUniversity of Traditional Medicine of Armenia (UTMA),Faculty of General Medicine,Yerevan,Armenia,0040Sahar LajmorakInstitute for Advanced Studies in Basic Sciences,Department of Earth Sciences,Zanjan,IranSimin GhorbaniAhvaz Jundishapur University of Medical Sciences,Faculty of Nursing,Department of Nursing and Midwifery,Ahvaz,IranParvin GhorbaniAhvaz Jundishapur University of Medical Sciences,Faculty of Medicine,Department of Cardiology,Ahvaz,IranNina KhlghatyanUniversity of Traditional Medicine of Armenia (UTMA),Faculty of General Medicine,Yerevan,Armenia,0040Harutyun StepanyanUniversity of Traditional Medicine of Armenia (UTMA),Faculty of General Medicine,Yerevan,Armenia,0040Samaneh BahramiHafez Institute of Higher Education,Faculty of English Litreture,Shiraz,IranSeyed Mohammad RasaeiUniversity of Traditional Medicine of Armenia (UTMA),Faculty of General Medicine,Yerevan,Armenia,0040Mehdi Ahmadi AlvarShahid Chamran University,Faculty of Engineering,Department of Computer Engineering,Ahwaz,IranRituraj RiturajObuda University,Doctoral School of Applied Informatics and Applied Mathematics,Budapest,Hungary
2023en
ABI

Аннотация

Breast cancer is the second leading cause of death after lung cancer. The only possible way to save patients' lives is early diagnosis of the disease; Because if this disease is diagnosed in the early stages and with a high level of accuracy, the chance of survival increases. Different fuzzy-based soft computing techniques have been proposed. In this research, the proposed fuzzy hybrid algorithm - particle swarm has been used to detect the type of breast tumors based on the analysis of features in mammography images. The proposed method in this study, the fuzzy hybrid algorithm - the proposed particle swarm algorithm, has a remarkable performance of 94.58% in breast cancer diagnosis. The results obtained from this study can be used for timely diagnosis and providing effective treatments for breast cancer.

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