Recent developments in data science in general and machine learning in particular have
transformed the way experts envision the future of surgery. Surgical Data Science (SDS) is a …

Modern endoscopy relies on digital technology, from high-resolution imaging sensors and
displays to electronics connecting configurable illumination and actuation systems for …

Out of all existing frameworks for surgical workflow analysis in endoscopic videos, action
triplet recognition stands out as the only one aiming to provide truly fine-grained and …

Context-aware decision support in the operating room can foster surgical safety and
efficiency by leveraging real-time feedback from surgical workflow analysis. Most existing …

Most benchmarks for studying surgical interventions focus on a specific challenge instead of
leveraging the intrinsic complementarity among different tasks. In this work, we present a …

Formalizing surgical activities as triplets of the used instruments, actions performed, and
target anatomies is becoming a gold standard approach for surgical activity modeling. The …

Large Vision-Language Models (LVLMs) are capable of handling diverse data types such as
imaging, text, and physiological signals, and can be applied in various fields. In the medical …

In addition to generating data and annotations, devising sensible data splitting strategies
and evaluation metrics is essential for the creation of a benchmark dataset. This practice …

Surgical action triplets describe instrument-tissue interactions as< instrument, verb, target>
combinations, thereby supporting a detailed analysis of surgical scene activities and …

Fine-grained medical action analysis plays a vital role in improving medical skill training
efficiency but it faces the problems of data and algorithm shortage. Cardiopulmonary …