Course detail

Computer-Aided Medical Diagnostics

FEKT-MPA-PRMAcad. year: 2024/2025

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

English

Number of ECTS credits

5

Mode of study

Not applicable.

Offered to foreign students

Of all faculties

Entry knowledge

The student should be able to explain fundamental principles of probability calculus, should know basic terms of data processing and should be oriented in basic knowledge of database systems. Generally, knowledge of mathematics on the level of Bachelor study is required.

Rules for evaluation and completion of the course

up to 30 points from individual project
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 aim of the course is to inform students about principles of computer-aided diagnostics in medicine using artifficial intelligence and design of simple diagnostics systems used in medicine.
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

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

O’Regan, G. Propositional and Predicate Logic. Springer, Cham 2017. ISBN 978-3-319-64020-4 (CS)
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

Not applicable.

Elearning

Classification of course in study plans

  • Programme MPA-BIO Master's 1 year of study, winter semester, compulsory
  • Programme MPC-BIO Master's 1 year of study, winter semester, compulsory
  • Programme MPAD-BIO Master's 1 year of study, winter semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

Syllabus

1. Definition of Clinical Decision Support
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

26 hod., compulsory

Teacher / Lecturer

Syllabus

1. CLIPS Basics I
2. CLIPS Basics II
3. Examples in CLIPS
4. Individual projects 

Elearning