Artificial intelligence assisted simulation and surgical video analytics for ophthalmic surgery training and...

Area of Science:

• Ophthalmology
• Medical Education
• Artificial Intelligence

Background:

• The Dreyfus model of skill acquisition provides a framework for understanding professional development in ophthalmology.
• Artificial intelligence (AI) is defined as data-driven algorithms for prediction, perception, and assessment using surgical data.
• Distinguishing AI from hardware like virtual reality (VR) is crucial for understanding its role in training.

Purpose of the Study:

• To classify ophthalmologist professional development into four stages: novice, advanced beginner, competent, and expert.
• To review the application of AI in ophthalmology training and practice.
• To explore how AI can augment surgical skills and decision-making.

Main Methods:

• Review of AI applications in VR simulation, surgical video analysis, and electronic health record (EHR) data.
• Classification of AI tools based on the Dreyfus model stages of skill acquisition.
• Analysis of AI's role in developing muscle memory, surgical logic, complication management, and expert technique benchmarking.

Main Results:

• Novice stage: AI in VR simulation builds muscle memory and standardized habits via haptic feedback and objective metrics.
• Advanced beginner stage: Computer vision and attention visualization aid workflow understanding and surgical logic.
• Competent stage: AI analyzes clinical data for complication risk and crisis training; Expert stage: AI benchmarks surgical techniques and identifies blind spots.

Conclusions:

• AI serves as an assistive tool to enhance ophthalmologist learning and decision-making across all professional stages.
• AI-enabled simulation, video analysis, and data-driven insights support continuous professional development.
• Key barriers to AI deployment include generalizability, interpretability, data governance, and medicolegal issues.