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 course: The course is aimed at students with a biomedical (medicine, biotech, biology) or technical (computer science, electrical engineering, maths, physics etc.) background.  Clinical Track: Basic experience in Basic Cardiology (Modul 11)  Tech Track:  Experience in ML&Web-Frameworks (PyTorch, Python-Flask) & JavaScript

Fachliche:r Betreuer:in

Univ.-Prof. Dr. med. Jeanette Schulz-Menger

Kontakt

richard.hickstein@charite.de

Link zum Vorlesungsverzeichnis

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