Course detail
Computer-Aided Medical Diagnostics
FEKT-MPA-PRMAcad. year: 2025/2026
The course is oriented ot the use of artifficial intelligence in medicine. It is focused on computer-aided medical diagnostics, principles of decision making in medicine, work with uncertainty in medical data, reasoning under uncertainty, principles of fuzzy representation of uncertain information, and structure of expert systems. Students will get experimental knowledge in programming of expert systems.
Language of instruction
Number of ECTS credits
Mode of study
Offered to foreign students
Entry knowledge
Rules for evaluation and completion of the course
up to 70 points from final written exam
The exam is oriented to verification of orientation in terms of computer-aided medical diagnostics and ability to apply basic principles of decision-making in medicine.
Aims
The student will be able to:
- describe basic methods of computer processing of biomedical data,
- explain fundamental terms of computer-aided medical diagnostics,
- describe principle of basic methods for probability decision-making,
- discus advantages and disadvantages of the methods,
- design simple expert systems,
- evaluate quality of decision-making methods based on defined requirements.
Study aids
Prerequisites and corequisites
Basic literature
Panesar, A. Machine Learning and AI for Healthcare. Springer, 2019. ISBN 978-1-4842-3799-1 (CS)
Russell, S. J., Norvig, P. Artificial Intelligence: A Modern Approach. Prentice Hall 2010. ISBN 9780136042594. (CS)
Recommended reading
Classification of course in study plans
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
2. Overview of Clinical Decision Support Systems
3. Probability in Decision Making - Discussion
4. Probability in Decision Making - Solution
5. Medical Reasoning and Thinking
6. Knowledge Representation
7. Probabilistic Reasoning in Medicine
8. Methods of Inference I
9. Methods of Inference II
10. Inference in Examples
11. Uncertainty and Inexact Reasoning
12. Approximate Reasoning
13. Fuzzy Logic Based Reasoning
Exercise in computer lab
Teacher / Lecturer
Syllabus
2. CLIPS Basics II
3. Examples in CLIPS
4. Individual projects