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 …

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 …

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 …

In this paper, appropriate and efficient networks for breast cancer knowledge discovery from
clinically collected data sets are investigated. Invoking various data mining techniques, it is …

While traditional medical informatics focus primarily on disease classification problems, the
disease survivability prediction for patients suffering from multi-stage conditions (eg …

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 …

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 …

Based on imbalanced data, the predictive models for 5-year survivability of breast cancer
using decision tree are proposed. After data preprocessing from SEER breast cancer …

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 …