Cancer is an aggressive disease with a low median survival rate. Ironically, the treatment
process is long and very costly due to its high recurrence and mortality rates. Accurate early …

Data mining and machine learning techniques are transforming the decision-making
process in the medical world. From using nomograms and expert advice, scientists are now …

This research studies a support vector machine (SVM)-based ensemble learning algorithm
for breast cancer diagnosis. Illness diagnosis plays a critical role in designating treatment …

Cancer is a fatal disease caused due to the undesirable spread of cells. Breast carcinoma is
the most invasive tumors and is the main reason for cancer deaths in females. Therefore …

Cancer is a life-threatening ailment characterized by the uncontrolled proliferation of cells.
Breast cancer (BC) represents the most highly infiltrative neoplasms and constitutes the …

One of the most critical issues of the mortality rate in the medical field in current times is
breast cancer. Nowadays, a large number of men and women are facing cancer-related …

Predicting breast cancer survival is crucial for practitioners to determine possible outcomes
and make better treatment plans for the patients. In this study, a hybrid data mining based …

Classification techniques have widely been applied to cancer survival prediction for
predicting survival or death of patients. However, little attention has been paid to patients …

Ovarian cancer is the third most common gynecologic cancers worldwide. Advanced ovarian
cancer patients bear a significant mortality rate. Survival estimation is essential for clinicians …

Background Breast cancer (BC) survival prediction can be a helpful tool for identifying
important factors selecting the effective treatment reducing mortality rates. This study aims to …