Machine Learning: A Literature Review for Breast Cancer

Abstract

Breast cancer is, after lung cancer, the most prevalent form of the disease in the globe. Women are the demographic most likely to be affected by this condition. Breast cancer is the most common kind of cancer to result in a woman's death if she is of childbearing age. Because there is always more to learn and there is room for improvement in every line of work, medical imaging is not an exception to this rule. It is expected that the death rate associated with cancer would decrease if it is discovered early and effectively treated. The diagnosis accuracy of persons working in the health care profession may be improved via the use of machine learning techniques. The technique known as deep learning has the potential to differentiate between breasts that are healthy and those that have cancer also known as neural networking. This method might be used to differentiate between healthy breast tissue and breast tissue affected by illness. Long-term research on the topic aimed, among other things, to examine breast cancer and screening practises among Indian women. This was one of the primary goals of the inquiry. A literature study was carried out with the assistance of several databases along with additional sources. Participants in the study were instructed to use phrases linked to breast cancer such as "breast carcinoma" and "breast cancer awareness," in addition to terms such as "knowledge" and "attitude," as well as the gender neutral term "women." In addition, India had a role in the study that was done. This search does not look for articles that have been published in the English language in the last 12 years.