Practical Course: Applied Deep Learning in Medicine

Jun 24, 2024

In this course students are given the chance to apply their abilities and knowledge in deep learning to real-world medical data. Students will be assigned a medical dataset and in close consultation with medical doctors create a project plan. Deep Learning methods will be applied to solve tasks to achieve the goal that is agreed upon. Datasets will be explored and analysed in several directions and different approaches will be evaluated and compared. In short this course offers students to:

Apply Deep Learning in the real world
Work on medical data and potentially help diagnose and analyse health related problems
Close supervision by PhD students with specialization in AI
Collaboration with medical experts
Work on the intersection between medicine and computer science

Prerequisites:

Completed at least one or several machine learning or deep learning courses (e.g. Intro to Deep Learning, Advanced Deep Learning, Machine Learning etc) with good grades. Knowledge about augmentation, optimizer, common model architectures, etc.
Good coding skills in python
Coding experience in one or more deep learning frameworks (Tensorflow, PyTorch, etc)
Enthusiasm for the application in the medical field

Objectives:

Ability to tackle applied deep learning projects in a structured manner with a good overview of possibilities
Gained insight into the problems of medical data
Final outcome as a useful insight or tool for medical professionals
If possible outcome will be published in a peer-reviewed venue