Related Experiment Videos
Artificial Intelligence-Driven Personalized Learning Improves Operating Room Instrument Training: A Prospective
Jing Cai1, Luping Li1, Jianshu Cai1
1Nursing Department, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine.
Journal of Visualized Experiments : Jove
|May 4, 2026
Summary
Artificial intelligence (AI) personalized learning systems significantly improve surgical instrument training. This AI-driven approach enhances long-term skill retention and patient safety compared to traditional methods.
Area of Science:
- Surgical Education
- Artificial Intelligence in Medicine
- Medical Simulation
Background:
- Traditional operating room instrument training suffers from poor skill retention and contributes to surgical errors.
- Current methods often lack personalization, leading to inefficiencies and suboptimal outcomes.
Purpose of the Study:
- To evaluate an AI-powered personalized learning system (APLS) for improving operating room instrument training.
- To assess the impact of APLS on technical competency, patient safety, and training efficiency.
Main Methods:
- Developed an APLS integrating learner phenotyping, deep learning, competency prediction, and reinforcement learning for adaptive feedback.
- Conducted a prospective observational study with 107 operating room staff comparing APLS to standard instructor-led training.
- Measured 12-month instrument-handling competency retention using the perioperative instrument proficiency scale (PIPS).
Main Results:
- APLS demonstrated substantially higher 12-month competency scores (84.1 vs. 58.9, p < 0.001) compared to traditional training.
- The AI system reduced safety incidents, halved training time, and decreased overall training costs by 38.3%.
- The AI ensemble outperformed individual machine learning components in performance prediction and feedback selection.
Conclusions:
- AI-powered personalized learning meaningfully enhances operating room instrument training.
- This approach improves skill retention, patient safety, and training efficiency.
- The APLS framework offers a scalable model for data-driven workforce development in perioperative care.