If you have a subscription to ChatGPT Plus, you can also try out the Medical AI Assistant (UiBmed - ELMED219 & BMED365) and see if you can get it to answer some of your questions.
ELMED219 examines how artificial intelligence and computational tools are shaping modern healthcare. It is offered in collaboration with the Department of Biomedicine at the University of Bergen (UiB), the Department of Computer Science, Electrical Engineering and Mathematical Sciences at the Western Norway University of Applied Sciences (HVL), and the Medical AI group at the Mohn Medical Imaging and Visualization Center (MMIV).
This course provides practical knowledge in computational thinking, medical imaging, and the use of machine learning and AI in healthcare. It also addresses ethical and regulatory challenges, giving students a balanced perspective on innovation in medical AI.
Through exercises and demonstrations, participants will work on practical applications, including analyzing MRI data, segmenting medical images, building biomarker prediction models, and exploring concepts like Patient similarity networks and multimodal data analysis. The course also introduces large language models (foundation models) and their potential use in healthcare.
Students will gain experience with Python programming, Jupyter notebooks, modern AI tools like ChatGPT, Gemini, and Claude, as well as cloud computing and AI-assisted coding. Emphasis is placed on open science and reproducible research practices to prepare students for both academic and practical settings.
The course includes a team project where students collaborate to design and build an AI-driven solution to a real healthcare challenge. Teams will take their ideas from concept to prototype and present them as a potential healthcare startup.
ELMED219 is an opportunity to gain valuable skills and insights into the use of AI in medicine and healthcare.
All course materials are openly available in this GitHub repository. See also BMED365.
Note: Students enrolled in the course can find additional practical information on MittUiB.
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For academic questions about the course, contact course coordinator Arvid Lundervold (UiB).
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For practical or administrative inquiries, contact the Studies Section at the Department of Biomedicine at [email protected]
The content for the course is offered with a CC BY-SA 4.0 license unless otherwise stated.
OBS: Some of the links are to earlier versions of the course. The content will soon be updated for the 2025 version
| TIME | ACTIVITY |
|---|---|
| WEEK 1: Fri, Jan 3 |
|
| On your own | Get an overview of the course; installation of software and/or test out Google Colab |
| Follow the instructions at setup.md and MittUiB | |
| WEEK 2: Mon, Jan 6 |
|
| 10:15-14:00 BB Hist 1 |
Information About the course Motivation lectures - Computational medicine - Medical AI - SW-installation - Tools |
| Arvid and Alexander Lundervold | |
| Wed, Jan 8 | |
| 14:15-16:00 BB Hist 1 |
AI-driven innovation in healthcare & About the course project |
| Arvid and Alexander Lundervold | |
| Fri, Jan 10 | |
| 10:15-11:30 BB Hist 1 |
LAB 0: Introduction to theory and tools for machine learning |
| Alexander Lundervold | |
| 11:45-13:00 BB Hist 1 |
LAB 1: Network science and patient similarity networks (PSN) |
| Arvid Lundervold | |
| WEEK 3: Tue, Jan 14 |
|
| 09:15-13:00 BB Hist 1 |
AI-assisted innovation cont. & Python programming; recap of Lab0, Lab1 |
| Arvid and Alexander Lundervold | |
| Fri, Jan 17 | |
| 08:15-13:00 BB Hist 1 |
Lab 2: Deep learning |
| Arvid Lundervold | |
| WEEK 4: Tue, Jan 21 |
|
| 09:15-12:00 BB Hist 1 |
Lab 3: Generative AI and Large Language Models |
| Alexander Lundervold | |
| 13:15-16:00 BB Hist 1 |
Meet-up for team project brainstorming and coaching |
| Arvid and Alexander Lundervold | |
| WEEK 5: Tue, Jan 28 |
|
| 08:15-10:00 BB Hist 1 |
Project presentations by team (jointly with BMED365) |
| Arvid and Alexander Lundervold | |
| Thu, Jan 30 | |
| 16:00 | Deadline for the Team Project Report - joint with BMED365 (hand in via MittUiB) |
| Fri, Jan 31 | |
|
Home exam: Duration: Expected workload Assignment is handed out: 31.01.2025, 11:00; Submission deadline: 31.01.2025, 15:00; Examination system: Inspera Digital exam |
"In Vivo Imaging and Physiological Modelling"
| Year | Link |
|---|---|
| 2021 | https://github.com/computational-medicine/BMED360-2021 |
| 2020 | https://github.com/computational-medicine/BMED360-2020 |
"Computational imaging, modelling and AI in biomedicine"
| Year | Link |
|---|---|
| 2024 | https://github.com/MMIV-ML/BMED365-2024 |