Course detail

Computer-Aided Medical Diagnostics

FEKT-MPA-PRMAcad. year: 2020/2021

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.

Guarantor

prof. Ing. Valentine Provazník, Ph.D.

Department

Department of Biomedical Engineering (UBMI)

Offered to foreign students

Of all faculties

Learning outcomes of the course unit

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.

Prerequisites

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.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Teaching methods include lectures and computer laboratories. Course is taking advantage of e-learning (Moodle) system. Students have to complete a project during the course.

Assesment methods and criteria linked to learning outcomes

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.

Course curriculum

1. Computer models for decision making
2. Uncertainty in medical informatics
3. Risk and uncertainty in decision making
4. Rationality in medicine
5. Searching for solutions to problems
6. Graph searching
7. Constraint satisfaction problem
8. Representation of knowledge
9. Inference
10. Propositional and predicate logic
11. Rule-based decision making
12. Logic programming
13. Natural language

Work placements

Not applicable.

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.

Specification of controlled education, way of implementation and compensation for absences

Not applicable.

Recommended optional programme components

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

eLearning: currently opened course

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

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

prof. Ing. Valentine Provazník, Ph.D.

Exercise in computer lab

26 hod., compulsory

Teacher / Lecturer

prof. Ing. Valentine Provazník, Ph.D.

Elearning

eLearning: currently opened course