AttyaLafta, H., KdhimAyoob, N. and Hussein, A.A. (2017) Breast Cancer Diagnosis Using Genetic Algorithm for Training Feed Forward Back Propagation. 2017 Annual Conference on New Trends in Information & Communications Technology Applications (NTICT), Baghdad, 7-9 March 2017, 144-149.
https://doi.org/10.1109/NTICT.2017.7976101

has been cited by the following article:

• TITLE: Impact of Genetic Algorithm for the Diagnosis of Breast Cancer: Literature Review

  AUTHORS: Abebe Alemu Balcha, Samuel Alemu Woldie

  KEYWORDS: Genetic Algorithm, Breast Cancer, Feature Classification, Optimization

  JOURNAL NAME: Advances in Infectious Diseases, Vol.13 No.1, February 27, 2023

  ABSTRACT: In recent research from the total number of new cancer cases in Africa about 29.46% and in Ethiopia 31.85% are breast cancer cases. 25.84% of all cancer related death is from breast cancer. One of the challenges in the treatment of breast cancer is early detection. Researchers agreed that, improving the preventive mechanism of breast cancer is an early predicting and detecting model. Research efforts are continuing to present different solution approaches using advanced techniques of Artificial intelligence (AI), Machine learning (ML), Deep Learning (DL), and Computational Intelligence as well. A genetic algorithm is a hyper-parameter optimization algorithm that belongs to the class of evolutionary algorithms. Genetic Algorithm (GA) is used for complex search spaces for search and optimization. This reviewed literature paper shows the positive effect of GA in the diagnosis of breast cancer on AI algorithms.