DAT350 Applied healthcare data science and medical physics
Credits (ECTS):10
Course responsible:Oliver Tomic
Campus / Online:Taught campus Ås
Teaching language:Engelsk
Course frequency:Annually
Nominal workload:Lectures: 78 hours. Exercises: 26 hours. Colloquia and self-study: 146 hours. Total 250 hours
Teaching and exam period: The starts in the autumn parallel. The course will be taught / graded in the autumn parallel.
About this course
DAT350 gives an introduction to machine learning methods relevant for analysis of healthcare data and fundamentals of medical physics. The following topics are covered:
- Survival analysis
- Principles of cancer and radiotherapy
- Medical imaging (CT, PET, MRI)
- Segmentation in medical images
- Biomarker engineering and feature extraction
- Feature selection for high-dimensional data
- Multiblock analysis methods for multi-source data
- Patient outcome prediction models
The course provides an introduction to the basic theoretical properties of the methods, but the main focus is on applied modelling with real datasets. The students will learn to make effective and models that, depending on the application, may support several FN sustainability goals, amongst others 3, 4, 9, 10 and 15.
Learning outcome
- The course will consist of lectures and practical exercises using computers and modern machine learning software (with help from teaching assistants).
Machine data analysis is a subject that constantly evolves, and online learning resources will be connected to lectures and exercises through the course webpages in Canvas.
The students can also request appointments with the lecturer in his/her office on pre-arranged times and via email.
DAT200 or similar
DAT300 or similar (can be taken at the same time)
INF120 or a similar course in basic programming (skills in Python are required)
INF200 or a similar course in advanced programming (version control and good programming practice are assumed to be known)
- FYS241A or similar
- Written exam, 3.5 hours. A-F.
- An external censor will participate together with the internal censor in forming the exam and censor guide. The external censor checks the internal censor's assessment of a random selection of candidates as a calibration at certain intervals in line with the faculty's guidelines for grading.
- Compulsory hand-in assignments. Rules for approving obligatory activities will be announced when the course starts.
- Lectures: 4 hours per week. Exercises: 2 hours per week.
- REALFAG