@article{article_1189743, title={Diagnosis of Breast Cancer with Hybrid Artificial Intelligence Method}, journal={Avrupa Bilim ve Teknoloji Dergisi}, pages={14–19}, year={2022}, DOI={10.31590/ejosat.1189743}, author={Çapkan, Hilal and Dönmez, Büşra and Kalkan, Gazi Muhammed and Kaya, Muhammed Zahid and Gürel, Sümeyye and Akdağlı, Eren and Tok, Yusuf Cafer and Şenol, Sevde Nur and Kandaz, Derya and Uçar, Muhammed Kürşad}, keywords={Breast Cancer, Hybrid Artificial Intelligence, Image Preprocessing, Feature Selection, Early Diagnosis}, 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.}, number={42}, publisher={Osman SAĞDIÇ}