Modeling and comparing data mining algorithms for prediction of recurrence of breast cancer.

ABSTRACT: Breast cancer is the most common invasive cancer and the second leading cause of cancer death in women. and regrettably, this rate is increasing every year. One of the aspects of all cancers, including breast cancer, is the recurrence of the disease, which causes painful consequences to the patients. Moreover, the practical application of data mining in the field of breast cancer can help to provide some necessary information and knowledge required by physicians for accurate prediction of breast cancer recurrence and better decision-making. The main objective of this study is to compare different data mining algorithms to select the most accurate model for predicting breast cancer recurrence. This study is cross-sectional and data gathering of this research performed from June 2018 to June

SUBMITTER: Mosayebi A 

PROVIDER: S-EPMC7561198 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature