Geographic information Systems-Biostatistics-medical informatics
| Title | ΓΕΩΓΡΑΦΙΚΑ ΣΥΣΤΗΜΑΤΑ ΠΛΗΡΟΦΟΡΙΩΝ-ΒΙΟΣΤΑΤΙΣΤΙΚΗ-ΙΑΤΡΙΚΗ ΠΛΗΡΟΦΟΡΙΚΗ / Geographic information Systems-Biostatistics-medical informatics |
| Code | ΜΠΙΒ008 |
| Cycle / Level | 2nd / Postgraduate |
| Teaching Period | Spring |
| Coordinator | Panagiotis Bamidis |
| Common | No |
| Status | Active |
| Course ID | 600017137 |
Programme of Study: PPS Health and Environmental Factors
Registered students: 50
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| Core | Compulsory Course | 2 | 1 | 6 |
| Academic Year | 2023 – 2024 |
| Class Period | Spring |
| Faculty Instructors |
|
| Instructors from Other Categories |
|
| Weekly Hours | 3 |
| Total Hours | 39 |
| Class ID | 600247320
|
Course Type 2021
Skills Development
Mode of Delivery
- Face to face
- Distance learning
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600247320
- eLearning: https://elearning.auth.gr/course/view.php?id=11997
Learning Outcomes
After successful completion of this module, students will be able to:
• Process biomedical data and draw safe conclusions.
• Understand statistical studies.
• To define basic statistical concepts such as the variable, statistical risk, errors.
• Construct correct questionnaires and draw correct scientific conclusions.
• To define basic concepts such as the map, its types, geographic systems, information systems, space geometry.
• To make use of IT applications in health.
• Appreciate the importance of biomedical technologies of augmented reality, virtual reality, robotics, artificial intelligence, 3D printing, tissue engineering and chatbots.
General Competences
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Adapt to new situations
- Work in an interdisciplinary team
- Generate new research ideas
- Design and manage projects
- Advance free, creative and causative thinking
Course Content (Syllabus)
1. MEDICAL INFORMATION
2. ARTIFICIAL INTELLIGENCE AND BIG DATA ANALYTICS
GLOBAL ENVIRONMENTAL PHENOMENA
3. HEALTHCARE APPLICATIONS
4. BIOSTATISTICS - MEDICAL STATISTICS
5. GEOGRAPHIC INFORMATION SYSTEMS
Educational Material Types
- Notes
- Slide presentations
- Video lectures
- Multimedia
- Interactive excersises
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Laboratory Teaching
- Use of ICT in Communication with Students
- Use of ICT in Student Assessment
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 50 | ✓ | ✓ | ||
| Reading Assigment | 50 | ✓ | ✓ | ||
| Written assigments | 40 | ✓ | |||
| Exams | ✓ | ||||
| Total | 140 |
Student Assessment
Student Assessment methods
- Written Exam with Multiple Choice Questions (Formative)
- Written Assignment (Summative)
- Report (Summative)
- Labortatory Assignment (Formative)
Bibliography
Additional bibliography for study
1. https://elearning.auth.gr/course/view.php?id=11997
2. Journal of Environmental Health - Advancing the Practice (Series of articles)
3. A system dynamics approach to understanding the One Health concept
4. Tracking environmental hazards and health outcomes to inform decision-making in the United States
5. Environmental Public Health Tracking Program Advances and Successes: Highlights From the First 15 Years
6. CDC’s National Environmental Public Health Tracking Program in Action: Case Studies From State and Local Health Departments
7. Electronic health record case studies to advance environmental public health
8. tracking
9. Data Science in Environmental Health Research
10. Big Data in Environment and Human Health
11. Promise and pitfalls in the application of big data to occupational and
12. environmental health
13. Bringing Big Data to Bear in Environmental Public Health: Challenges and Recommendations
14. Interdisciplinary data science to advance environmental health research and improve birth outcomes
15. Dynamic assessment of PM2.5 exposure and health risk using remote sensing and geo-spatial big data
16. Is Artificial Intelligence Revolutionizing Environmental Health?
17. A Hybrid Approach to Identifying Key Factors in Environmental Health Studies
18. Special Issue "Data Science for Environment and Health Applications"
19. Informatics and Data Analytics to Support Exposome-Based Discovery for Public Health
20. The exposome: a new paradigm to study the impact of environment on health Exposome and Exposomics
Last Update
03-01-2024
