Data mining has the most important role in healthcare for discovering hidden relationships in
big datasets, especially in breast cancer diagnostics, which is the most popular cause of …

Breast cancer is one of the main causes of female fatality all over the world and is the major
field of research since quite a long time with lesser improvement than expected. Many …

While there are many factors which could contribute to the occurrence of breast cancer, it is
very difficult to attribute the exact environmental and other factors contributing to it, but still it …

Feature selection, which picks the optimal subset of characteristics related to the target data
by deleting unnecessary data, is one of the most important aspects of the machine learning …

Breast cancer represents one of the diseases that make a high number of deaths every year.
It is the most common type of all cancers and the main cause of women's deaths worldwide …

Every year around one million women are diagnosed with breast cancer. Conventionally it
seems like a disease of the developed countries, but the fatality rate in low and middle …

Objective (s): This study addresses feature selection for breast cancer diagnosis. The
present process uses a wrapper approach using GA-based on feature selection and PS …

Breast cancer is the most common cancer among women (43.3 incidents per 100.000
women), with the highest mortality (14.3 incidents per 100.000 women). Early detection is …

Classification and data mining methods are an effective way to classify data, especially in
medical field, where those methods are widely used in diagnosis and analysis to make …

There are more than 100 types of cancer around the world with different symptoms and
difficulty in predicting itsappearance in a person due to its random and sudden attack …