Purpose Surgical workflow and skill analysis are key technologies for the next generation of
cognitive surgical assistance systems. These systems could increase the safety of the …

Objective: To provide an overview of ML models and data streams utilized for automated
surgical phase recognition. Background: Phase recognition identifies different steps and …

Surgical workflow recognition has numerous potential medical applications, such as the
automatic indexing of surgical video databases and the optimization of real-time operating …

Automatic surgical phase recognition is a challenging and crucial task with the potential to
improve patient safety and become an integral part of intra-operative decision-support …

Background Automatic surgical workflow recognition is a key component for developing the
context-aware computer-assisted surgery (CA-CAS) systems. However, automatic surgical …

The need for automatic surgical skills assessment is increasing, especially because manual
feedback from senior surgeons observing junior surgeons is prone to subjectivity and time …

Background Surgical process modeling automatically identifies surgical phases, and further
improvement in recognition accuracy is expected with deep learning. Surgical tool or time …

Background Technical skill assessment in surgery relies on expert opinion. Therefore, it is
time-consuming, costly, and often lacks objectivity. Analysis of intraoperative data by artificial …

Objective skill assessment-based personal performance feedback is a vital part of surgical
training. Either kinematic—acquired through surgical robotic systems, mounted sensors on …

Objective: In the last two decades, there has been a growing interest in exploring surgical
procedures with statistical models to analyze operations at different semantic levels. This …