H.6.3.2. Feature evaluation and selection
1. H-BwoaSvm: A Hybrid Model for Classification and Feature Selection of Mammography Screening Behavior Data

E. Enayati; Z. Hassani; M. Moodi

Volume 8, Issue 2 , Spring 2020, , Pages 237-245

Abstract
  Breast cancer is one of the most common cancer in the world. Early detection of cancers cause significantly reduce in morbidity rate and treatment costs. Mammography is a known effective diagnosis method of breast cancer. A way for mammography screening behavior identification is women's awareness evaluation ...  Read More

H.3. Artificial Intelligence
2. A New Knowledge-Based System for Diagnosis of Breast Cancer by a combination of the Affinity Propagation and Firefly Algorithms

N. Emami; A. Pakzad

Volume 7, Issue 1 , Winter 2019, , Pages 59-68

Abstract
  Breast cancer has become a widespread disease around the world in young women. Expert systems, developed by data mining techniques, are valuable tools in diagnosis of breast cancer and can help physicians for decision making process. This paper presents a new hybrid data mining approach to classify two ...  Read More

F.4.17. Survival analysis
3. Extracting Predictor Variables to Construct Breast Cancer Survivability Model with Class Imbalance Problem

S. Miri Rostami; M. Ahmadzadeh

Volume 6, Issue 2 , Summer 2018, , Pages 263-276

Abstract
  Application of data mining methods as a decision support system has a great benefit to predict survival of new patients. It also has a great potential for health researchers to investigate the relationship between risk factors and cancer survival. But due to the imbalanced nature of datasets associated ...  Read More