Detecting Breast Cancer through Blood Analysis Data using Classification Algorithms

Oladosu Oladimeji; Olayanju Oladimeji

Volume 9, Issue 3 , July 2021, , Pages 351-359

http://dx.doi.org/10.22044/jadm.2021.9839.2116

Abstract
  Breast cancer is the second major cause of death and accounts for 16% of all cancer deaths worldwide. Most of the methods of detecting breast cancer are very expensive and difficult to interpret such as mammography. There are also limitations such as cumulative radiation exposure, over-diagnosis, false ...  Read More

H.6.3.2. Feature evaluation and selection
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 , April 2020, , Pages 237-245

http://dx.doi.org/10.22044/jadm.2020.8105.1945

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
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 , January 2019, , Pages 59-68

http://dx.doi.org/10.22044/jadm.2018.6489.1763

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
Extracting Predictor Variables to Construct Breast Cancer Survivability Model with Class Imbalance Problem

S. Miri Rostami; M. Ahmadzadeh

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

http://dx.doi.org/10.22044/jadm.2017.5061.1609

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