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Course info
KIV / UMI
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Course description
Department/Unit / Abbreviation
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KIV
/
UMI
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Academic Year
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2023/2024
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Academic Year
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2023/2024
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Title
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Introduction to Medical Informatics
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Form of course completion
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Pre-Exam Credit
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Form of course completion
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Pre-Exam Credit
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Accredited / Credits
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Yes,
3
Cred.
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Type of completion
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Combined
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Type of completion
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Combined
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Time requirements
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Lecture
2
[Hours/Week]
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Course credit prior to examination
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No
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Course credit prior to examination
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No
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Automatic acceptance of credit before examination
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No
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Included in study average
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NO
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Language of instruction
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Czech
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Occ/max
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Automatic acceptance of credit before examination
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No
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Summer semester
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0 / -
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0 / -
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0 / -
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Included in study average
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NO
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Winter semester
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3 / -
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1 / -
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0 / -
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Repeated registration
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NO
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Repeated registration
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NO
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Timetable
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Yes
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Semester taught
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Winter semester
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Semester taught
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Winter semester
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Minimum (B + C) students
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5
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Optional course |
Yes
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Optional course
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Yes
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Language of instruction
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Czech
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Internship duration
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0
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No. of hours of on-premise lessons |
0
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Evaluation scale |
S|N |
Periodicity |
každý rok
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Periodicita upřesnění |
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Fundamental theoretical course |
Yes
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Fundamental course |
No
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Fundamental theoretical course |
Yes
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Evaluation scale |
S|N |
Substituted course
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None
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Preclusive courses
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N/A
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Prerequisite courses
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N/A
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Informally recommended courses
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N/A
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Courses depending on this Course
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KIV/MISZ
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Histogram of students' grades over the years:
Graphic PNG
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XLS
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Course objectives:
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The course's goal is to provide the fundamental theoretical knowledge of key topics of medical informatics, such as the acquisition and representation of data, information, and knowledge in healthcare, exploring information technology for clinical decision support, or ethical aspects of research involving human subjects. So, it provides the students with an overview of the current medical informatics and related fields. Mastering more profound theoretical knowledge and related practical skills is a subject of specialized, more generally conceived courses: KIV/DBM2, KIV/VI, KIV/SU, KIV/AZS, KIV/ZVI, etc.
The course is designed for graduate studies and it is recommended for enrolment in the 1st semester.
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Requirements on student
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In order to pass the course, a student must:
1) actively participate in at least 50% of lectures, whereas the activity means asking qualified questions and making relevant contributions to the discussions, based especially on self-study of the peer-reviewed papers provided by the lecturer (about 5-6 per semester, typically on a biweekly basis) and personal and professional background;
2) submit a short reflection (about 1-2 paragraphs) on at least 10 out of 12 key topics, including what essential they learned, how they will (or may) use it in their further study or professional carrier, and recommendations on what to change in the course in the future;
3) individually or in pairs, write a seminar paper on a topic in the field of biomedical informatics, which will include a systematic review of relevant literature (typically written in English) and producing an analytical solution to the given professional problem;
4) and pass the final (summary) test.
The deadline for obtaining credit is 31.1.
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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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Activities
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Fields of study
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Předmět má vedené stránky na CourseWare (https://courseware.zcu.cz/portal/studium/courseware/kiv/umi), kde jsou pro studenty k dispozici:
1) kompletní prezentace z přednášek
2) veškerá povinná a doporučená literatura (ve formátu PDF)
Pro předmět existuje zřízený Discord server UMI (pozvánka je rozesílána zapsaným studentům před zahájením semestru), kde studenti mezi sebou nebo s vyučujícími mohou řešit problémy s řešením semestrální práce, ale i diskutovat zkouškové příklady apod. Odezvy od vyučujících jsou do 24 hodin, většinou "okamžité".
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Guarantors and lecturers
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Literature
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Time requirements
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All forms of study
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Activities
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Time requirements for activity [h]
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Contact hours
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26
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Preparation for comprehensive test (10-40)
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15
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Graduate study programme term essay (40-50)
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30
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Total
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71
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Prerequisites
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Knowledge - students are expected to possess the following knowledge before the course commences to finish it successfully: |
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 - students are expected to possess the following skills before the course commences to finish it successfully: |
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 - students are expected to possess the following competences before the course commences to finish it successfully: |
N/A |
N/A |
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Learning outcomes
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Knowledge - knowledge resulting from the course: |
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 - skills resulting from the course: |
clearly present the medical informatics method described in a paper written in English |
Competences - competences resulting from the course: |
identify the graduate courses relevant for their specific area of interest in medical informatics |
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Assessment methods
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Knowledge - knowledge achieved by taking this course are verified by the following means: |
Continuous assessment |
Individual presentation at a seminar |
Test |
Skills - skills achieved by taking this course are verified by the following means: |
Individual presentation at a seminar |
Continuous assessment |
Competences - competence achieved by taking this course are verified by the following means: |
Formative evaluation |
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Teaching methods
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Knowledge - the following training methods are used to achieve the required knowledge: |
Lecture supplemented with a discussion |
Interactive lecture |
Self-study of literature |
Individual study |
Skills - the following training methods are used to achieve the required skills: |
Self-study of literature |
Competences - the following training methods are used to achieve the required competences: |
Discussion |
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