Diagnosis of Breast Cancer with Hybrid Artificial Intelligence Method

Authors : Hilal ÇAPKAN, Büşra DÖNMEZ, Gazi Muhammed KALKAN, Muhammed Zahid KAYA, Sümeyye GÜREL, Eren AKDAĞLI, Yusuf Cafer TOK, Sevde Nur ŞENOL, Derya KANDAZ, Muhammed Kürşad UÇAR

Pages : 14-19

Doi:10.31590/ejosat.1189743

View : 119 | Download : 15

Publication Date : 2022-10-31

Article Type : Research Paper

Abstract :According to the data of 2020, it is seen that 1 of every eight cancers diagnosed worldwide and the 5th among cancers that cause death is breast cancer. Cancer can spread to different organs and reach an incurable stage in patients who are not diagnosed and treated at the right time. Therefore, reducing the time taken for breast cancer diagnosis and reducing mortality rates are of great importance for accurate and early diagnosis of the disease. This study aims to improve the accuracy of cancer detection by using various machine learning algorithms and methods for artificial intelligence-based breast cancer diagnosis. By using ultrasonography images taken from 780 people, image information processed with statistical parameters was extracted. Artificial intelligence-based breast cancer detection was performed by applying three different machine learning algorithms and the hybrid machine learning algorithm designed as a combination of these algorithms on the extracted data set. In this way, early detection of cancerous cells will be carried out without creating advanced risks for the individual, and treatment will be possible.
Keywords : Meme Kanseri, Hibrit Yapay Zeka, Görüntü İşleme, Özellik Seçimi, Erken Teşhis

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