A new artificial intelligence system could revolutionize how surgeons are trained by providing objective, standardized feedback on surgical technique using nothing more than a smartphone camera and a downloadable app. Currently, surgical trainees receive feedback that varies widely depending on who's teaching them and where they train, making it difficult to ensure consistent quality. A vascular surgery resident at UC Davis Health is developing a computer vision-based AI model designed to change that, with potential implications for surgical training in resource-limited countries and even board certification processes.

Why Is Standardized Surgical Feedback So Hard to Find?

Right now, there's no universally accepted method for objectively assessing technical skill across surgical specialties. Feedback from experienced surgeons is often subjective and can differ dramatically between institutions and educators. This inconsistency means that two surgeons trained in different places might have very different levels of proficiency, even if they both pass their exams. The problem becomes even more acute in parts of the world where formal surgical training programs don't exist at all.

"Currently, there is no strong, universally accepted method for objectively assessing technical skill across surgical specialties. Feedback is often subjective and varies widely between institutions and educators," explained Keenan Gibson, the vascular surgery resident leading the project.

Keenan Gibson, Vascular Surgery Resident at UC Davis Health

Gibson's motivation for tackling this problem came from firsthand experience. Earlier this year, he traveled to Ghana on a medical mission trip, where he discovered that the country lacks a formal vascular surgery training program entirely. Access to specialized surgical care is extremely limited, and many patients go untreated simply because there aren't enough trained surgeons. During conversations with local surgeons and residents, Gibson realized that the barriers to surgical education went far beyond just lacking equipment.

How Can AI Help Surgeons Train Without an Expert in the Room?

Gibson's solution is elegantly simple: a low-resource, smartphone-based AI training platform. Surgical trainees record themselves performing simulated procedures on 3D-printed models. The AI model then analyzes their technique and delivers structured, objective feedback, eliminating the need for a senior surgeon to be physically present. This is particularly valuable in settings where finding an expert surgeon available for continuous oversight simply isn't realistic.

The system works by training the AI on video recordings of surgical procedures, teaching it to recognize proper technique and identify areas for improvement. Because it's video-based, it can assess multiple aspects of surgical performance simultaneously, from hand positioning to instrument handling to procedural flow. The feedback is standardized, meaning every trainee gets evaluated using the same criteria, regardless of where they're training.

Steps to Deploy AI-Assisted Surgical Training Globally

• Develop 3D-Printed Models: Create affordable, anatomically accurate surgical models that trainees can practice on without expensive equipment or access to operating rooms.
• Train the AI System: Feed the computer vision model thousands of hours of recorded surgical procedures to teach it what proper technique looks like and how to identify errors.
• Validate Performance: Test the AI's feedback against assessments from experienced surgeons to ensure accuracy and reliability before widespread deployment.
• Integrate Real-Time Guidance: Eventually, the system could provide live feedback during actual procedures by analyzing a patient's specific anatomy beforehand using 3D-printed models.
• Incorporate into Board Certification: Once fully validated, the AI assessment could become part of the official vascular surgery board certification process, ensuring all surgeons meet consistent proficiency standards.

Gibson has already begun designing and 3D-printing low-cost surgical models that can be distributed internationally. The beauty of this approach is that it doesn't require expensive simulators or specialized surgical instruments. Trainees simply need access to the models and a smartphone with a camera. The AI does the rest, providing the consistent, structured feedback that would normally require an expert surgeon to be present.

The project received a grant from the Association of Program Directors in Vascular Surgery (APDVS), recognizing its potential to address a critical gap in surgical education. Once the model has been fully validated, Gibson plans to expand its capabilities. One particularly innovative application involves using highly accurate 3D-printed models of a patient's specific anatomy to train the AI before surgery begins. This would allow the system to provide real-time guidance during actual vascular procedures, an approach that isn't possible with existing training methods.

"What this project offers is a truly deployable training resource. In many parts of the world, building a comprehensive surgical training program just isn't realistic, which leaves far too many patients untreated due to a lack of trained specialists," Gibson stated.

Keenan Gibson, Vascular Surgery Resident at UC Davis Health

The implications extend far beyond individual trainees. Better-trained surgeons lead to better patient outcomes, fewer complications, and more efficient procedures. In countries where surgical expertise is scarce, this technology could help close a critical gap in healthcare access. By making high-quality surgical education available to trainees regardless of their geographic location or access to senior surgeons, the AI system has the potential to improve surgical care for millions of patients worldwide.

Gibson's work represents a broader trend in healthcare technology: using artificial intelligence not to replace human expertise, but to democratize access to it. The system doesn't eliminate the need for experienced surgeons; instead, it extends their knowledge and standards to places where they simply can't be physically present. As the technology matures and becomes more widely adopted, it could fundamentally reshape how surgical training happens globally.