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One of the most significant concerns around the world has been human health. So far, there have been little discussion about how the Computer Science can help to improve diagnostics of many diseases. In this paper, the aim is to prove that the Computer Science can offer techniques to help the improvement of the diagnosis of medical pathologies. For that, Feature Subset Selection and Typical Testors will be applied to a breast cancer database. Nowadays, cancer is a medical condition difficult to ignore, which has special interest by the specialists for finding effective methods to prevent and cure it. The database contains a feature set of breast cancer cells, which were subjected to an analysis of testors in order to find the minimum feature set that best describes benign and malignant cells. As a result, each typical testor found contains risk factors recognized by medical experts.

Feature Subset Selection and Typical Testors Applied to Breast Cancer Cells