Machine learning in health technology - from basic knowledge to application of machine learning (2025)
Doctoral School in Medicine, Biomedical Science and Technology at Aalborg University
Welcome to MACHINE LEARNING IN HEALTH TECHNOLOGY - FROM BASIC KNOWLEDGE TO APPLICATION OF MACHINE LEARNING
Program: BEN
Description:
Do you want to get into machine learning but do not know where to start? This is a 3-day course with a practical approach to machine learning directed to PhD students at the Faculty of Medicine. The course includes two days of lectures from basics about machine learning to application of models and critical interpretation of the results. Students will be able to work on their own data (or data provided by the lecturers) based on learnings from the first two days and on the third day, results, and plans for optimizing their results will be discussed.
The content of the course is:
- Getting started with machine learning
- Extracting information from data and identifying the most relevant sources (Feature extraction and reduction of feature space)
- Classification and regression models
- Evaluating the performance of a model
- Working with own data
The lecturers will use Python in teaching, but the principles and concepts are easily transferred to other environments, such as, R, MATLAB, etc.
Prerequisites:
An education in health sciences and basic knowledge about statistical concepts.
Form of evaluation:
The students will be evaluated individually through their work with own data or data provided by the lecturers.
Key literature:
Links to pre read distributed in Moodle by the different lecturers in due time before the course.
Organizer: Associate Professor Thomas Kronborg Larsen, email: tkl@hst.aau.dk
Lecturers: Associate Professor Thomas Kronborg Larsen, Associate Professor Lasse Riis Østergaard
ECTS: 2.0
Time: 12, 13 November, and 15 December 2025 (08.15 – 16.15)
Deadline: 22 October 2025
Place: Aalborg University
Zip code: 9220
City: Aalborg
Maximal number of participants: 25