How AI is used in Surgical Education

Over the past two decades, surgical education has undergone a profound makeover.

Traditional apprenticeships have evolved into competency-based training, tailored to the demands of the 21st century. The volume of knowledge has surged exponentially, challenging surgical trainees to keep up.

Simultaneously, surgical techniques have advanced, transitioning from open procedures to minimally invasive and image-guided methods.

These innovations demand extensive and extended training to attain proficiency.

Lately, AI has emerged as a potent force capable of reshaping healthcare and surgical education.

Skill Acquisition

The rapid evolution of surgical innovation has outpaced advancements in surgical training. Reduced operative experience during residency, owing to restricted work hours and increased administrative responsibilities, poses a significant challenge.

Virtual-reality (VR)-based training, complemented by AI and machine learning, can bridge this gap.

VR platforms offer hands-on training experiences, while AI provides unbiased personalized feedback to enhance skill acquisition.

Surgical Simulation

Machine learning, a subset of AI, can analyze VR simulation data to offer real-time feedback and facilitate skill development. This combination creates immersive training experiences and ensures trainees are well-prepared before they enter the operating room.

Intraoperative Guidance

Accurate performance assessment is essential for surgical trainees to become competent and safe surgeons.

Robotic surgery platforms, equipped with AI, can analyze data generated during surgery, providing objective skill assessments and constructive feedback. These platforms can track movements, speeds, and other metrics to assess the surgeon's proficiency.

AI can also analyze surgical videos to support decision-making, improve surgical quality, and enhance patient outcomes. For instance, AI models can efficiently identify whether specific critical surgical views have been achieved.