Breast Cancer Stereotypes

Breast cancer is one of the most common diseases and primary cause of the huge number of deaths among women worldwide. Early detection methods and exact diagnostics are essential to the success of breast cancer treatment. However, breast cancer is a heterogeneous disease that is caused by a variety of genes. Therefore an understanding of the differences between breast cancer subtypes has become the primary avenue for treatment. In order to get a deep understanding of the various subtypes, classifying cancer patients by molecular features and phenotypic of cancer subtype will be needed. To fulfill this need, Computer Scientists and Medical Researchers in the bioinformatics field have partnered together to use a high performance data science

method and its techniques. This data science method is machine learning and its data mining and analytical technologies.Their efforts will be concentrated on the classification, modeling, and analysis of breast cancer datasets containing genomic and clinical information. Machine learning will be used due to its ability to detect patterns and derive insight from complex datasets to support in the decision making process. Although machine learning can be applied to and improve any process in the medical field, a level of validation is required in order for its implementation to be considered in everyday clinical practices.