Predicting the survival status of patients who will undergo breast cancer surgery is highly
important, where it indicates whether conducting a surgery is the best solution for the …

Breast cancer is a major threat for middle aged women throughout the world and currently
this is the second most threatening cause of cancer death in women. But early detection and …

In this paper, we described the practical application of data mining methods for estimation of
survival rate and disease relapse for breast cancer patients. A comparative study of …

Cancer is the most common death causing disease and breast cancer is the deadliest
cancer affecting women universally. Survivability forecast of a patient after breast cancer …

This research uses breast cancer data from the Surveillance, Epidemiology, and End
Results (SEER) dataset's (1973-2010), which contains 684394 records. It is cleaned using …

Machine learning algorithms are computer programs that try to predict cancer type based on
the past data. The eventual goal of Machine learning algorithms in cancer diagnosis is to …

In this paper, we report on our experiments with SEER data and the problem of five-year
survivability prediction using logistic regression. This work provides a detailed process for …

Medical informatics mainly deals with finding solutions for the issues related to the diagnosis
and prognosis of various deadly diseases using machine learning and data mining …

Breast cancer is the most common cancer in women and thus the early stage detection in
breast cancer can provide potential advantage in the treatment of this disease. Early …

In the last decade, the use of data mining techniques has become widely accepted in
medical applications, especially in predicting cancer patients' survival. In this study, we …