The course is offered by the Department of Biomedicine in collaboration with the Department of Computer science, Electrical engineering and Mathematical sciences, Western Norway University of Applied Sciences, and the Mohn Medical Imaging and Visualization Center.
During the course you will gain insight into computationally oriented thinking, machine learning and artificial intelligence, and an understanding of the pros and cons of AI for the future of medicine. The course provides a guided tour through some biomedical and clinical applications of mathematical and statistical modeling techniques, as well as principles for selected sensors and measuring instruments in research and clinical practice.
We meet concepts such as big data, data analysis, machine learning, and artificial intelligence (AI), with examples from personalized and predictive medicine. You will use methods and tools from numerical programming, data analysis and "scientific computing" for medical applications, and learn about the importance of open science, data sharing, and reproducible research.
This repository contains most of the course material. Students enrolled in the course will also find some practical information at MittUiB.
A presentation and reflection on the course (aimed for the "Kunstig intelligens i norsk helsetjeneste (KIN)" network meeting, February 8th 2022) is found here.
For academic questions about the course, contact course coordinator Arvid Lundervold (UiB) or Alexander S. Lundervold (HVL).
For practical / administrative inquiries, contact the Studies Section at the Department of Biomedicine at studie.biomed@uib.no
The content for the course is offered with a CC BY-SA 4.0 license unless otherwise stated.
| TIME | ACTIVITY (NOTE: access to links will be provided in due time) |
|---|---|
| Mon/Tue January 3-4 | |
| On your own | Get an overview of the course; installation of software and/or test out Google Colab |
| Follow the instructions at MittUiB | |
| Tue, Jan 4 | |
| 10:15-12:00 12.30-13.15 |
About the course / Motivation lectures 1-slides-about, 1-PDF-slides-about, 1-video-about 2-slides-CompMed, 2-PDF-slides-CompMed, 2-video-CompMed 3-PDF-slides-medAI, 3-video-medAI |
| Arvid Lundervold / Alexander Selvikvåg Lundervold | |
| Wed, Jan 5 | |
| 12:15-14:00 | Tools, teams and project work 4-slides-tools, 4-PDF-slides-tools, 4-video-tools 5-slides-team-project, 5-PDF-slides-team-project, 5-video-team-project |
| Arvid Lundervold / Alexander Selvikvåg Lundervold | |
| Thu, Jan 6 | |
| 10:15-11:00 | LAB 0: Introduction to theory and tools for machine learning |
| Alexander Selvikvåg Lundervold | |
| 11:15-12:00 | Brain imaging (MRI) in glioblastoma slides-brain-imaging, video-brain-imaging Lab 0.2-MRI (optional): Digital imaging and image analysis focusing on MRI with a view to IMC |
| Arvid Lundervold | |
| January 6 - January 11 | |
| On your own | You'll spend approximately four hours completing a DataCamp course (remember to use the link on MittUiB for free access to DataCamp). The rest of day you'll work on your course projects. Which DataCamp course you're encouraged to do depends on your previous programming experience: - No Python programming experience? Complete the course Introduction to Python - Know some Python, but no machine learning? Can pass the Python Programming Assessment in our DataCamp group? Complete the course Supervised Learning with scikit-learn - Know the fundamentals of machine learning in Python? Can pass the Machine Learning Fundamentals Assessment? Complete the course Biomedical Image Analysis in Python |
| Tue, Jan 11 | |
| 10:15-11:00 | LAB 1: Structured medical health records |
| Alexander Selvikvåg Lundervold | |
| 12:15-13:00 | LAB 2: Natural language processing |
| Alexander Selvikvåg Lundervold | |
| Thu, Jan 13 | |
| 10:15-12:00 | LAB 3: A quick introduction to deep learning |
| Alexander Selvikvåg Lundervold | |
| Video-Some additional information about the course project | |
| Mon, Jan 17 | |
| 10:15-11:00 | LAB 4: BRATS and multimodal MRI |
| Arvid Lundervold | |
| Fri, Jan 21 | |
| 10:15-12:00 | Perspectives on medical AI: innovation, education, epistemology, ethics and impact PDF-slides-perspectives, video-perspectives |
| Arvid Lundervold / Alexander Selvikvåg Lundervold | |
| Mon, Jan 24 | |
| --- 17:00 --- | Team project report due |
| Wed, Jan 26 | |
| 10:15-12:00 | Team project presentations (15 min) |
| Fri, Jan 28 | |
| 09:00-11:00 | Digital home exam (using Inspera) |