Artificial Intelligence-Assisted Surgery: Potential and Challenges

Abstract

Background: Artificial intelligence (AI) has recently achieved considerable success in different domains including medical applications. Although current advances are expected to impact surgery, up until now AI has not been able to leverage its full potential due to several challenges that are specific to that field.

Summary: This review summarizes data-driven methods and technologies needed as a prerequisite for different AI-based assistance functions in the operating room. Potential effects of AI usage in surgery will be highlighted, concluding with ongoing challenges to enabling AI for surgery.

Key messages: AI-assisted surgery will enable data-driven decision-making via decision support systems and cognitive robotic assistance. The use of AI for workflow analysis will help provide appropriate assistance in the right context. The requirements for such assistance must be defined by surgeons in close cooperation with computer scientists and engineers. Once the existing challenges will have been solved, AI assistance has the potential to improve patient care by supporting the surgeon without replacing him or her.

Keywords: Artificial intelligence in surgery; Cognitive surgical robotics; Robot-assisted surgery; Sensor-enhanced operating room; Surgical data science; Workflow analysis.

Fig. 1

Potential of artificial intelligence (AI) in surgery based on a sensor-enhanced operating room (SensorOR).

Fig. 2

Left: example of generating synthetic images based on simple laparoscopic simulations. Middle: generative adversarial networks translate these images so they look like real laparoscopic images. These images, along with their generated labels, can be used without further annotation effort. Right: machine-learning-based detection of the surgical phase and prediction of the duration of the remaining procedure during laparoscopic cholecystectomy.