450-4049/01 – Applied Artificial Intelligence Methods (AUI)

Gurantor departmentDepartment of Cybernetics and Biomedical EngineeringCredits4
Subject guarantordoc. Ing. Martin Černý, Ph.D.Subject version guarantordoc. Ing. Martin Černý, Ph.D.
Study levelundergraduate or graduateRequirementOptional
YearSemesterwinter
Study languageCzech
Year of introduction2010/2011Year of cancellation
Intended for the facultiesFEIIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
CER275 doc. Ing. Martin Černý, Ph.D.
KUB631 Ing. Jan Kubíček, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Graded credit 2+2
Combined Graded credit 2+12

Subject aims expressed by acquired skills and competences

The subject represents the introduction to the principles of scientific field of artificial intelligence. The goal of subject is introduce students on analysis and design of artificial intelligence tolls in the field of biomedical engineering. Students will be ready for practical use of basic artificial intelligence tools namely fuzzy expert systems, artificial neural networks and genetic algorithms in the field of BME.

Teaching methods

Lectures
Tutorials
Experimental work in labs

Summary

Subject deals with gathering of knowledge and applications of the artificial intelligence methods in the context of processing and modeling of the biomedical image data. Subject is composed from four main areas of the artificial intelligence. The first part of the subject deals with the fuzzy mathematics, fuzzy modeling, and design of the expert systems. The second part of the subject deals with the data classification with emphasis to an area of the neural network. Next area deals with optimization techniques with emphasis of an analysis of the genetic algorithms for solving of the complex mathematical problems. The last part of the subject focuses to hierarchical and non-hierarchical methods of the cluster analysis.

Compulsory literature:

RUSSEL,S., NORVIG,P.: Artificial Intelligence, Prentice-Hall, Inc., 2003, ISBN 0-13-080302-2 LUGER,G.F., STUBBLEFIELD,W.A.: Artificial Intelligence, The Benjamin/Cummings Publishing Company, Inc., 2009, ISBN-13: 978-0-321-54589-3 ISBN-10: 0-321-54589-3 ZIMMERMANN,H.J. Fuzzy Set Theory - and Its Applications. Kluwer Academic Publishers, 2001. ISBN-13: 978-0792374350 HUDSON, D. L. a M. E. COHEN. Neural networks and artificial intelligence for biomedical engineering. New York: Institute of Electrical and Electronics Engineers, c2000. ISBN 978-0780334045. AGAH, Arvin. Medical applications of artificial intelligence. Boca Raton: CRC Press/Taylor & Francis Group, 2014. ISBN 9781439884331.

Recommended literature:

C. R. REEVES, J. E. ROW,. Genetic Algorithms: Principles and Perspectives. Kluwer Academic Publishers, New York, 2002. GRAUPE,D. Principles of Artificial Neural Netvorks. World Scientific. 2013. ISBN: 978-981-4522-73-1 BEGG, Rezaul., Daniel T. H. LAI a Marimuthu. PALANISWAMI. Computational intelligence in biomedical engineering. Boca Raton: CRC Press, c2008. ISBN 9780849340802. SHUKLA, Anupam a Ritu TIWARI. Intelligent medical technologies and biomedical engineering: tools and applications. Hershey, PA: Medical Information Science Reference, c2010. ISBN 1615209778.

Way of continuous check of knowledge in the course of semester

Verification of study: The current activity of student is done through his laboratories activities. Conditions for graded credit: Student can gain up to 40 points from the laboratory excercices. To pass the laboratory part of the course student has to gain at least 21 points To pass the course student has to pass both of the laboratory part of the course and the final written proof 60, min 30 points.

E-learning

Další požadavky na studenta

There are not defined other requirements for students

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

Lectures: 1. Introduction on artificial intelligence scientific field 2. Principles of artificial intelligence, importace of knowledge in problem solving tasks 3. Methods of computer knowledge reprezentation 4. Mathematic and linguistc modelling 5. Vagueness formalization of knowledge in linguistic models 6. Principles of fuzzy set and fuzy logic theory 7. Fuzzy models of Mandami type 8. Fuzzy models of Takagi-Sugeno type 9. Diagnostoc expert systems 10. Fuzzy controllers 11. Topology and functions of multilayer artificial neural networks 12. Neural networks application in biomedical engineering 13. Genetic algorithms - versatil optimization methods 14. Genetic algorithms application in adaptation procedures Laboratories: 1. Fuzzy controller using microcomputer and PLC Computer labs: 1. Computer system MATLAB 2. Fuzzy ToolBox in MATLAB 3. Fuzzy sets and vagueness objects reprezentation in MATLAB 4. Fuzzy conditonal rules formalization in MATLAB 5. Fuzzy modelling of Mandami type in MATLAB 6. Fuzzy modelling of Takagi-Sugeno type in MATLAB 7. Diagnostic fuzzy expert systems 8. Fuzzy controllers in MATLAB 9. Pletysmogram evaluation fuzzy expert module 10. EEG evaluation fuzzy expert module 11. Neural network synthesi in Neural ToolBoxu of MATLABu 12. Neural network application in biomedical engineering 13. Genetic algorithm synthesis in MATLAB

Conditions for subject completion

Full-time form (validity from: 2010/2011 Winter semester, validity until: 2013/2014 Summer semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Graded exercises evaluation Graded credit 100 (100) 51
        Laboratory works Laboratory work 60  45
        Written proof Other task type 40  6
Mandatory attendence parzicipation:

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Occurrence in study plans

Academic yearProgrammeField of studySpec.FormStudy language Tut. centreYearWSType of duty
2019/2020 (N2649) Electrical Engineering (3901T009) Biomedical Engineering P Czech Ostrava Optional study plan
2019/2020 (N2649) Electrical Engineering (3901T009) Biomedical Engineering K Czech Ostrava Optional study plan
2018/2019 (N2649) Electrical Engineering (3901T009) Biomedical Engineering P Czech Ostrava Optional study plan
2018/2019 (N2649) Electrical Engineering (3901T009) Biomedical Engineering K Czech Ostrava Optional study plan
2017/2018 (N2649) Electrical Engineering (3901T009) Biomedical Engineering K Czech Ostrava Optional study plan
2017/2018 (N2649) Electrical Engineering (3901T009) Biomedical Engineering P Czech Ostrava Optional study plan
2016/2017 (N2649) Electrical Engineering (3901T009) Biomedical Engineering K Czech Ostrava Optional study plan
2016/2017 (N2649) Electrical Engineering (3901T009) Biomedical Engineering P Czech Ostrava Optional study plan
2015/2016 (N2649) Electrical Engineering (3901T009) Biomedical Engineering K Czech Ostrava Optional study plan
2015/2016 (N2649) Electrical Engineering (3901T009) Biomedical Engineering P Czech Ostrava Optional study plan
2014/2015 (N2649) Electrical Engineering (3901T009) Biomedical Engineering K Czech Ostrava Optional study plan
2014/2015 (N2649) Electrical Engineering (3901T009) Biomedical Engineering P Czech Ostrava Optional study plan
2013/2014 (N2649) Electrical Engineering (3901T009) Biomedical Engineering P Czech Ostrava Optional study plan
2013/2014 (N2649) Electrical Engineering (3901T009) Biomedical Engineering K Czech Ostrava Optional study plan
2012/2013 (N2649) Electrical Engineering (3901T009) Biomedical Engineering P Czech Ostrava Optional study plan
2012/2013 (N2649) Electrical Engineering (3901T009) Biomedical Engineering K Czech Ostrava Optional study plan
2011/2012 (N2649) Electrical Engineering (3901T009) Biomedical Engineering P Czech Ostrava Optional study plan
2011/2012 (N2649) Electrical Engineering (3901T009) Biomedical Engineering K Czech Ostrava Optional study plan
2010/2011 (N2649) Electrical Engineering (3901T009) Biomedical Engineering P Czech Ostrava 1 Optional study plan
2010/2011 (N2649) Electrical Engineering (3901T009) Biomedical Engineering P Czech Ostrava 2 Optional study plan
2010/2011 (N2649) Electrical Engineering (3901T009) Biomedical Engineering K Czech Ostrava 1 Optional study plan
2010/2011 (N2649) Electrical Engineering (3901T009) Biomedical Engineering K Czech Ostrava 2 Optional study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner