In diesem Wintersemester wird die im WiSe 2022/23 erfolgreich gestartete Vortragsreihe Medical Information Sciences fortgesetzt. Renommierte Wissenschaftlerinnen und Wissenschaftler unterschiedlicher Fachdisziplinen und Forschungsstandorte geben jeden Donnerstag ab 16:00 Uhr Einblicke in aktuelle Fragestellungen und Anwendungsgebiete des breiten Forschungsfeldes Medical Information Sciences.

Surgical Data Science is a rapidly evolving interdisciplinary field that aims to improve the quality, safety, and value of interventional healthcare through data acquisition, organization, analysis, and modeling. Over the past decade, advances in deep learning, computational power, and collaborative medical data initiatives have driven significant progress in computer vision and natural language processing within the surgical domain.

This talk will explore the emerging role of foundation models, large models pre-trained on broad data using self-supervised learning, and their ability on a wide range of clinically relevant tasks, often with minimal labeled data. I will review recent surgical image and video-based foundation model developments, discuss key downstream applications, and highlight common pitfalls in benchmarking their performance. Additionally, I will present current strategies for leveraging large language models (LLMs) to standardize surgical metadata and improve data interoperability at scale.