How AI-Powered Video Analytics Helped Improve Surgical Training Outcomes
In an era where surgical video data is more accessible than ever, the real challenge isn’t just recording cases—it’s transforming them into meaningful learning opportunities. That’s exactly what Dr. Daniel Moreno set out to do with his groundbreaking study using SurgeryView.ai, the surgical intelligence platform developed by Genesis MedTech.
Over the course of a year, Dr. Moreno applied AI analytics to over 400 laparoscopic sleeve gastrectomy cases, uncovering new insights into surgical performance, trainee progression, and the power of data to drive improvement.
🎓 The Goal: Quantifying Progress in Surgical Training
Dr. Moreno’s primary aim was to evaluate how trainees evolved over time—and whether AI-assisted video review could support more objective feedback and faster skill acquisition.
He focused on three core areas:
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Step-specific procedure duration
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Longitudinal trends across cases
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The relationship between case complexity and performance
Unlike traditional training, which relies heavily on subjective assessments and anecdotal feedback, SurgeryView.ai enabled objective benchmarking through automated phase segmentation, peer comparison, and factor analysis (such as BMI, age, and diabetes status).
🔍 The Study
Across 405 sleeve gastrectomy procedures, Dr. Moreno and his team used SurgeryView.ai’s AI engine to:
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Automatically segment videos into surgical steps
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Track procedure time by step and overall
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Compare individual performance to peer benchmarks
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Identify improvement trends over time
Using this data, he was able to isolate key inflection points in each trainee’s journey—pinpointing exactly when a fellow was improving and where they still needed support.
📈 The Results
The findings were both promising and practical:
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18.92% overall reduction in procedure time
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27.91% improvement in Step 2 (greater curvature dissection)
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15.37% improvement in Step 5 (final sleeve shaping)
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Clear, trackable progression in technical performance across repeated cases
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Enhanced ability to correlate patient factors (like BMI or diabetes status) with case complexity
By integrating AI-driven insights, Dr. Moreno turned hundreds of videos into a structured, data-rich training ecosystem. Fellows could not only watch their own performance—but also see how they stacked up against peers and how their efficiency evolved over time.
🧠 Why It Matters
This study highlights a growing truth in surgical education: video is no longer just a tool for reflection—it’s a data source.
With platforms like SurgeryView.ai, we can now:
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Automate feedback loops for both individuals and training programs
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Quantify growth in real time
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Standardize assessment without interrupting clinical workflow
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And empower surgeons to make evidence-based improvements
“SurgeryView.ai offers a powerful insight into surgical performance and growth — a much-needed tool for assessing technical skill and guiding training.”
— Dr. Daniel Moreno, Bariatric Surgeon, Tijuana Mexico
🔗 What’s Next?
As AI tools continue to evolve, so does our ability to create more personalized, outcome-driven surgical education. Dr. Moreno’s work is a blueprint for what’s possible when technology and training converge—and a reminder that with the right data, growth becomes not just a goal, but a trackable journey
Learn More about SurgeryView
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