Course detail

Computer-Aided Medical Diagnostics

FEKT-MPA-PRMAcad. year: 2023/2024

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

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 computer exercises (10 points test and 20 points 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.

The exam from the subject will take place online.


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

Russell, S. J., Norvig, P. Artificial Intelligence: A Modern Approach. Prentice Hall 2010. ISBN 9780136042594. (CS)
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)

Recommended reading

Not applicable.


Classification of course in study plans

  • 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



26 hours, optionally

Teacher / Lecturer

Exercise in computer lab

26 hours, compulsory

Teacher / Lecturer