2025S

Science and Technology

Carsten Marr
Institut für Kunst und Gesellschaft, Cross-Disciplinary Strategies
2025S, wissenschaftliches Seminar (SEW), 4.0 ECTS, 2.0 SemStd., LV-Nr. S05327

Beschreibung

The use of artificial intelligence (AI) is transforming essential aspects of our lives. In biomedical and clinical research, AI models are being trained to perform expert tasks in standardized and automated ways. This development raises not only medical, but also ethical and legislative questions that society must address.

In this course, we will:

  1. Learn fundamental concepts of AI, machine learning, and mathematical modeling.
  2. Study applications of these technologies in biomedicine through current publications.
  3. Collaboratively develop ideas on how to address and present important and controversial topics in this field.

Students will gain comprehensive insights into the possibilities and challenges of AI in biomedicine and develop critical thinking skills regarding the societal impacts of these technologies.

 

Prüfungsmodalitäten

Participants will be evaluated based on course presence, participation in discussions, and their project presentations

Anmerkungen

Please bring your laptops!

Some reading on the topic:

- Eric Topol: Deep Medicine

https://www.newyorker.com/magazine/2019/07/22/the-promise-and-price-of-cellular-therapies

- https://www.science.org/doi/10.1126/science.aax2342

Schlagwörter

biomedicine, artificial intelligence, mathematical models, data analysis, deep neural networks

Termine

05. Mai 2025, 10:00–16:00 CDS Studio
07. Mai 2025, 10:00–14:30 CDS Studio
08. Mai 2025, 10:00–16:30 CDS Studio
09. Mai 2025, 10:00–16:00 CDS Studio

LV-Anmeldung

Ab 03. Februar 2025, 00:00
Per Online Anmeldung

Cross-Disciplinary Strategies (Master): Studienfelder 1-3: Studienfeld 2: Wissenschaft und Technologie 569/020.02

Cross-Disciplinary Strategies (Bachelor): Wissenschaft und Technologie: Vertiefungs-/Anwendungsphase 700/002.20

Mitbelegung: möglich

Besuch einzelner Lehrveranstaltungen: möglich