SELECTED TOPICS IN COMPUTATIONAL INTELLIGENCE II (6 Credits)

Learning Outcomes:

On successful completion of this course, students will be able to: Understand the concepts of Intelligent Computing and capable to use the concepts for solving real world problems; Undertand how various soft computing techniques such as neural net (NN), fuzzy inference system (FIS), and genetic algorithms (GA) are applied for breast cancers detection, clustering and classifications.

Topics:

1. Introduction to Computational Intelligence;
2. Digital Mammography and Early Stage of Breast Cancer Detection & Diagnosis;
3. Theory and Concepts of Artificial Neural Networks;
4. Neural Network Applied for Mammogram Classification (Review Papers);
5. Writing Experimental Computation Papers on Mammogram Classification Using Special Features and Neural Net Classifiers;
6. Theory and Concept Fuzzy System;
7. Writing Experimental Computation Papers on Mammogram Clustering Using Special Features and Fuzzy Classifiers;
8. Neural Network and Fuzzy Neural for Breast Cancers Diagnosis;
9. Theory and Concept Evolutionary Computation (Genetic Algorithms);
10. Optimization Using Genetic Algorithms;
11. Writing Experimental Computation papers on Mammogram Clustering Using Special Features and Hybrid Classifiers;
12. Digital Mammography and Early Stage of Breast Cancer Detection & Diagnosis