Course: Introduction to Medical Informatics

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Course title Introduction to Medical Informatics
Course code KIV/UMI
Organizational form of instruction Lecture
Level of course Master
Year of study not specified
Semester Winter
Number of ECTS credits 3
Language of instruction Czech
Status of course unspecified
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Kohout Josef, Doc. Ing. Ph.D.
Course content
1. Modern Trends in Health Care: 4P Medicine 2. Biomedical Data, Information, and Knowledge 3. Research Integrity in Biomedicine 4. mHealth and Wearable Technology 5. Stratification Biomarkers in Personalised Medicine 6. Biomedical Data Registration 7. Biomedical data fusion 8. Electronic Health Record, Data Standards in Medical Informatics 9. Design and Development of Clinical Decision Support Systems 10. Information Systems in Health Care 11. Biomedical data and information visualization 12. Neuroinformatics 13. Invited presentation, revisions

Learning activities and teaching methods
  • Contact hours - 26 hours per semester
  • Graduate study programme term essay (40-50) - 30 hours per semester
  • Preparation for comprehensive test (10-40) - 15 hours per semester
prerequisite
Knowledge
demonstrate knowledge of the basic principles of the theory of differential and integral calculus of functions of one or more real variables (KMA/MA2 or KMA/M2)
understand the basic principles of linear algebra (KMA/LAA)
formulate a statistical hypothesis and select a suitable statistical test for the hypothesis test (KMA/PSA)
Demonstrate knowledge of basic data structures used in computer science (stack, queue, special search trees, dictionaries, hash tables, sets, graphs) (KIV/PT or KIV/ADS)
Skills
use English at least at level B2 of the Common European Framework of Reference for Languages (UJP / AEP4, etc.)
calculate the probability and conditional probability of a phenomenon (KMA/PSA)
design and implement more complex algorithms for processing heterogeneous data (KIV/PPA2 or KIV/ADS, KIV/ALG or KIV/PRO, KIV/PC, and other)
Competences
N/A
N/A
learning outcomes
Knowledge
explain what biomedical/medical/healthcare informatics, bioinformatics, and neuroinformatics deals with
explain the role of information technology in health care
describe the nature of the data used typically in biomedicine
describe at a general level the process leading from data acquisition to computer-aided diagnosis
explain the data registration process and describe the principles of ICP (Iterative Closest Points) method
understand the basic concepts of medical informatics: mHealth, eHealth, telemedicine, EHR
be familiar with standards ICD-10 (11), HL7, DASTA, DICOM, etc.
describe the principles for conducting responsible research involving human subjects (either directly or indirectly)
Skills
clearly present the medical informatics method described in a paper written in English
Competences
identify the graduate courses relevant for their specific area of interest in medical informatics
teaching methods
Knowledge
Lecture supplemented with a discussion
Interactive lecture
Self-study of literature
Individual study
Skills
Self-study of literature
Competences
Discussion
assessment methods
Knowledge
Continuous assessment
Individual presentation at a seminar
Test
Skills
Individual presentation at a seminar
Continuous assessment
Competences
Formative evaluation
Recommended literature
  • Selected readings from peer-reviewed literature in biomedical informatics and related as specified on CourseWare.
  • Edward H. Shortliffe, James J. Cimino. Biomedical Informatics - Computer Applications in Health Care and Biomedicine. 2021. ISBN 978-3-030-58720-8.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester