DAT350 Applied Healthcare Data Science and Medical Physics

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.