Motivation and objective: Emergency medicine is becoming a popular application area for
artificial intelligence methods but remains less investigated than other healthcare branches …

In clinical settings, most automatic recognition systems use visual or sensory data to
recognize activities. These systems cannot recognize activities that rely on verbal …

In this study, we propose a deep learning framework and a self-supervision scheme for
video-based surgical gesture recognition. The proposed framework is modular. First, a 3D …

Surgical phase recognition is a basic component for different context-aware applications in
computer-and robot-assisted surgery. In recent years, several methods for automatic …

The fine-grained localization of clinicians in the operating room (OR) is a key component to
design the new generation of OR support systems. Computer vision models for person pixel …

Surgical robotics holds much promise for improving patient safety and clinician experience
in the Operating Room (OR). However, it also comes with new challenges, requiring strong …

Surgical workflow analysis is essential to help optimize surgery by encouraging efficient
communication and the use of resources. However, the performance of phase recognition is …

Objective Trauma resuscitation is the initial evaluation and management of injured patients
in the emergency department. This time-critical process requires the simultaneous pursuit of …

Understanding the workflow of surgical procedures in complex operating rooms requires a
deep understanding of the interactions between clinicians and their environment. Surgical …

There has been a growing interest in using deep learning models for processing long
surgical videos, in order to automatically detect clinical/operational activities and extract …