Data
Official data in SubjectManager for the following academic year: 2024-2025
Course director
Kvell Krisztián
associate professor,
Department of Pharmaceutical Biotechnology
Number of hours/semester
Lectures: 0 hours
Practices: 0 hours
Seminars: 14 hours
Total of: 14 hours
Subject data
- Code of subject: OPF-IAI-T
- 1 Credit
- Pharmacy
- Optional module
- autumn
haven't
Course headcount limitations
min. 5 people – max. 24 people
Topic
Students with background on computer engineering and pharmaceutics/biotechnology will collaborate on a project using AI on data related to biomedical or health technology. As technology revolutionizes healthcare, understanding the principles and applications of AI is crucial for advancing drug discovery, personalized medicine, and therapeutic development. The project is part of two courses running at University of Pécs (PTE) and University of South-Eastern Norway (USN).
Lectures
Practices
Seminars
- 1.
Recreuitment: Gathering Campus-credit students at PTE for EDUC course
- Kvell Krisztián, Pál Szilárd - 2.
Introduction: Meeting and information for all students interested in COIL
- Kvell Krisztián, Pál Szilárd - 3.
Start of project: Defining project, group members and project scope
- Kvell Krisztián, Pál Szilárd - 4.
Implementation I: Collect data
- Kvell Krisztián, Pál Szilárd - 5.
Implementation II: Develop working model
- Kvell Krisztián, Pál Szilárd - 6.
Implementation III: Finalize working model
- Kvell Krisztián, Pál Szilárd - 7.
Testing: Test the model and consider ethical dilemmas
- Kvell Krisztián, Pál Szilárd - 8.
Presentation: Present project online
- Kvell Krisztián, Pál Szilárd - 9.
Conclusion: Discussion and concluding remarks
- Kvell Krisztián, Pál Szilárd - 10.
Take home messages: Final discussion with Campus-credit students of PTE
- Kvell Krisztián, Pál Szilárd - 11.
Az EDUC kurzus tapasztalatainak összegyűjtése
- Kvell Krisztián, Pál Szilárd - 12.
Az EDUC kurzus tapasztalatainak elemzése
- Kvell Krisztián, Pál Szilárd - 13.
Az EDUC kurzus továbbfejlesztése
- Kvell Krisztián, Pál Szilárd - 14.
Az EDUC kurzus konklúzióinak egyeztetése hazai és nemzetközi, szakmai és adminisztratív partnereinkkel
- Kvell Krisztián, Pál Szilárd
Reading material
Obligatory literature
Literature developed by the Department
Notes
Recommended literature
Explainable Artificial Intelligence for Biomedical Applications (River Publishers, ISBN: 978-8770228497, by Utku Kose, Deepak Gupta and Xi Chen)
Conditions for acceptance of the semester
Successful project work and group presentation.
Mid-term exams
Written test on basics then project work.
Making up for missed classes
Project work is not time or space limited, maybe done at home, anytime.
Exam topics/questions
Test questions will focus on basics, but project work presentation is decisive.
Examiners
- Kvell Krisztián
- Pál Szilárd
Instructor / tutor of practices and seminars
- Kvell Krisztián
- Pál Szilárd