Tuesday 16:15−17:30 or on appointment
Room 45.2.102 or online
At the core of the digitalisation and automation in medicine is the intelligent processing of sensor and other input data. Using and developing artificial intelligence for medical systems requires an understanding of the underlying processes and mechanisms. Technologies are rapidly evolving and more and more medical applications are benefitting from machine learning approaches. The aim of our seminars is to gain deep knowledge about recent trends in signal processing and applied machine learning to process biomedical data and signals. The participants will study, critically assess, and present recent literature and technological advancements of artificial intelligence (AI) in medicine that drive developments in this exciting research field.
The student learns and practices to
A list of relevant topics will be provided on moodle at the beginning of the semester. A topic is picked in the first week and the student will elaborate a literature research on this focus topic.
You will analyse the literature and technologies specific to a topic of your choice. During self-guided work you will elaborate a manuscript that covers your literature research. In a final presentation you will be presenting your results. You will get support by input lectures providing you the basics of scientific work and presentation skills. Peer-review will be also practiced to illustrate processes of scientific dissemination.
These modules are designed for master and doctroal students. They are also available to medical students, held in German and in a slightly adapted form to fit into their curriculum: MED12345.075 - W 658 Aktuelle Forschung der Künstlichen Intelligenz in der Medizin verstehen und erfolgreich präsentieren
The information displayed on this page is for general information only and may not be complete. For legal binding information, please consult the currently active Modulhandbuch/FSPO of the respective study program. Day-to-day information is provided through the moodle page of the respective course (registration required).