Inhalte

Learning Outcomes: Practical research experience in a multidisciplinary research environment consisting of medical and technical researchers. Content: Supervised multidisciplinary Research Project applying machine-learning (ML) and web-application development to 3D-quantitative tissue characterization in cardiovascular magnetic resonance imaging (CMR) for healthy-cohorts and cardiomyopathy patients. Description of Teaching and Learning Methods • Structured Onboarding Phase • Supervised Clinical and Tech Tracks • weekly meetings/discussions between groups • Clinical: Image analysis and User Feedback • Tech: Model and App Development Desirable prerequisites for participation in the courses: The course is aimed at students with a biomedical (medicine, biotech, biology) or technical (computer science, electrical engineering, maths, physics etc.) background. Clinical Track: Experience in Basic Cardiology (Modul 11) Tech Track: Experience in ML&Web-Frameworks (PyTorch, Python-Flask) & JavaScript. 

Fachliche:r Betreuer:in

Prof. Dr. Jeanette Schulz-Menger

Kontakt

richard.hickstein@charite.de

Link zum Vorlesungsverzeichnis

Link