Breast cancer classification using a constructed convolutional neural network on the basis of the histopathological images by an interactive web-based interface

In this study, it is aimed to develop a system that can provide clinical support to physicians in the diagnosis of breast cancer with open source access artificial intelligence based software. The proposed system was designed using an open source data set for the classification of breast cancer (benign/malignant) on the basis of the histopathological images. In this context, Keras library and convolutional neural networks from deep learning methods were used on the images obtained by staining with hematoxylin and eosin of biopsy specimens taken from breast tissues. Shiny package in the R programming language is employed to develop for the user interface. According to the experimental results obtained from the study, it was determined that the designed system gives promising predictions in the classification of breast cancer and can be used for clinical decision support in the classification of the disease. This designed system can be available at http://biostatapps.inonu.edu.tr/MKSY/ in both English and Turkish.