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 …

Most surgeons are skeptical as to the feasibility of autonomous actions in surgery.
Interestingly, many examples of autonomous actions already exist and have been around for …

Telesurgical robotics, as a technical solution for robot-assisted minimally invasive surgery
(RAMIS), has become the first domain within medicosurgical robotics that achieved a true …

Surgical robots have been widely adopted with over 4000 robots being used in practice
daily. However, these are telerobots that are fully controlled by skilled human surgeons …

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 …

Many keyhole interventions rely on bi-manual handling of surgical instruments, forcing the
main surgeon to rely on a second surgeon to act as a camera assistant. In addition to the …

Recent advances in machine learning models allowed robots to identify objects on a
perceptual nonsymbolic level (eg, through sensor fusion and natural language …

Poorly annotated data is a common problem for data-intensive applications like supervised
machine learning. In domains like healthcare, annotation tasks require specific domain …

Background In surgical advancements, robot-assisted surgery (RAS) holds several promises
like shorter hospital stays, reduced complications, and improved technical capabilities over …

Surgery faces a paradigm shift since it has developed rapidly in recent decades, becoming a
high-tech discipline. Increasingly powerful technological developments such as modern …