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Lecturer(s)
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Schlecht Miroslav, doc. Ing. Ph.D.
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Course content
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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
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Learning activities and teaching methods
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- 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
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| prerequisite |
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| Knowledge |
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| 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 |
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| 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 |
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| N/A |
| N/A |
| learning outcomes |
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| Knowledge |
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| 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 |
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| clearly present the medical informatics method described in a paper written in English |
| Competences |
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| identify the graduate courses relevant for their specific area of interest in medical informatics |
| teaching methods |
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| Knowledge |
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| Lecture supplemented with a discussion |
| Interactive lecture |
| Self-study of literature |
| Individual study |
| Skills |
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| Self-study of literature |
| Competences |
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| Discussion |
| assessment methods |
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| Knowledge |
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| Continuous assessment |
| Individual presentation at a seminar |
| Test |
| Skills |
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| Individual presentation at a seminar |
| Continuous assessment |
| Competences |
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| Formative evaluation |
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Recommended literature
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Selected readings from peer-reviewed literature in biomedical informatics and related as specified on CourseWare.
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Edward H. Shortliffe, James J. Cimino. Biomedical Informatics - Computer Applications in Health Care and Biomedicine. 2021. ISBN 978-3-030-58720-8.
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