Data Mining and Machine Learning Approaches in Breast Cancer Biomedical Research

Background

In human body, if the cells in the breast are started to grow without any control, it leads to cancer. Normally, the growth of the lump can be seen using x-ray. The affected cells can propagate into nearby tissues or blowout all over the body. More than 100 types of cancer are identified in the medical field and it became one of the major roots of death in the world. There are many factors that influence the formation and spreading of cancers which are listed below:

• 1.

  Genetics

• 2.

  Gender

• 3.

  Age

• 4.

  Life style

• 5.

  Environment

• 6.

  Marital status

Breast cancer is the deadliest disease which is a malevolent cell development in the breast. The cancer cells extend to other parts of the body, if the patient left untreated. The occurrence of breast cancer upsurges after 40 years of age. The incidence of this disease is even high with women over age 50. Breast cancer causes deaths in women which has the second place among other diseases. According to the survey, mortality rates dropped significantly during 1992-1998 with the major decreases in younger women. Breast cancer is most prevalent in women which affect over 13% of all women in the world. There is more number of younger women vulnerable to breast cancer in most of the nations (Richie & Swanson, 2003).

Breast cancer is of two types. They are:

• 1.

  Harmless breast lump (non-cancerous): The texture and the size of tumor are easy to understand through the basic examination;

• 2.

  Malignant breast lump (cancerous): Diagnosis of clinical studies needed for predicting this kind of cancer. This type can be further categorized into:

  • a.

    Non-invasive: Affected cells have not extended in other cells and tissues;

  • b.

    Invasive: Affected cells have extended into the neighboring cells and tissues.