Using data mining techniques for diagnosis and prognosis of cancer disease

TL;DR

This paper reviews data mining techniques applied to breast cancer diagnosis and prognosis, highlighting recent research efforts to improve early detection and prediction of cancer recurrence.

Contribution

It provides a comprehensive overview of data mining approaches used in breast cancer diagnosis and prognosis, emphasizing recent advancements and research trends.

Findings

Data mining improves accuracy in breast cancer diagnosis.

Recent techniques enhance prognosis predictions.

Summarizes current research and methodologies.

Abstract

Breast cancer is one of the leading cancers for women in developed countries including India. It is the second most common cause of cancer death in women. The high incidence of breast cancer in women has increased significantly in the last years. In this paper we have discussed various data mining approaches that have been utilized for breast cancer diagnosis and prognosis. Breast Cancer Diagnosis is distinguishing of benign from malignant breast lumps and Breast Cancer Prognosis predicts when Breast Cancer is to recur in patients that have had their cancers excised. This study paper summarizes various review and technical articles on breast cancer diagnosis and prognosis also we focus on current research being carried out using the data mining techniques to enhance the breast cancer diagnosis and prognosis.