Seminar - Graph Deep Learning for Medical Applications (IN0014, IN2107, IN4431)

Lecturer (assistant)
Duration2 SWS
TermSommersemester 2022
Language of instructionEnglish
Position within curriculaSee TUMonline
DatesSee TUMonline


Admission information

See TUMonline
Note: Please register in the matching system for the course registration ( Interested students should attend the preliminary meeting. This semester we will have a joint presentation of the CAMP MedIA courses offered, on Thursday, February 3rd, 2022, from 10:00 to 11:30 AM with the following agenda: Machine Learning in Medical Imaging (MLMI): 10:00 hrs. - 10:30 hrs. Deep Learning for Medical Applications (DLMA): 10:30 hrs. - 11:00 hrs. Graph Deep Learning for Medical Applications (GDLMA): 11:00 hrs. - 11:30 hrs. Feel free to attend all the talks of your interest. The sessions will be conducted in zoom: Meeting ID: 676 3521 2467 Passcode: 535230 Interested students should attend the preliminary meeting. Link to the webpage:


Graph Deep Learning is a new exotic branch in many fields like computer Vision and Medical Imaging. Many real-world medical and non-medical datasets can be represented in the form of graphs, providing a powerful source of information for machine learning models. This graph-based data, combined with the success of the convolutional neural networks, has motivated to translate the key ingredients of deep learning models into the graph domain. Many communities such as healthcare, social media, and computer vision are moving towards analysing the data using Graph Convolutions. This seminar provides a space for discussion of the recent scientific publications on GCN with a focus on their medical applications and others.


Deep learning, machine learning