Breast cancer is the second leading cause of death for women, so accurate early detection
can help decrease breast cancer mortality rates. Computer-aided detection allows …

Background Using visual, biological, and electronic health records data as the sole input
source, pretrained convolutional neural networks and conventional machine learning …

Breast cancer disease is the second most common world cause of cancer death in women.
However, the early diagnostics and detection can provide a significant chance for correct …

This paper presents a comparison of six machine learning (ML) algorithms: GRU-SVM [1],
Linear Regression, Multilayer Perceptron (MLP), Nearest Neighbor (NN) search, Softmax …

Globally, breast cancer is one of the most significant causes of death among women. Early
detection accompanied by prompt treatment can reduce the risk of death due to breast …

Breast cancer affects one out of eight females worldwide. It is diagnosed by detecting the
malignancy of the cells of breast tissue. Modern medical image processing techniques work …

For the past decade, machine learning technology has increasingly become popular and it
has been contributing to many areas that have the potential to influence the society …

Logical analysis of data (LAD), an approach to data analysis based on Boolean functions,
combinatorics, and optimization, can be considered one of the methods of interpretable …

The purpose of this study is to develop an intelligent remote detection and diagnosis system
for breast cancer based on cytological images. First, this paper presents a fully automated …

The use of machine learning (ML) and data mining algorithms in the diagnosis of breast
cancer (BC) has recently received a lot of attention. The majority of these efforts, however …