Objective:

To address the specific challenges in training specialists for diagnosing and treating retinopathy of prematurity (ROP), including the shortage of trained professionals and the limitations of traditional training methods.

Key Findings:

• XR simulation allows for practice without patient risk, enhancing procedural skills and confidence.
• AI can provide objective performance metrics and structured feedback, facilitating personalized learning.
• Training programs can be scaled to meet the demand for ROP specialists globally, particularly in underserved regions.

Interpretation:

The integration of XR and AI in surgical training can significantly improve the competency of trainees, ultimately reducing preventable childhood blindness due to ROP by ensuring a well-trained workforce.

Limitations:

• XR simulation cannot fully replicate the clinical experience and tactile feedback of real patient interactions, which are crucial for developing clinical judgment.
• There remains a need for actual clinical exposure alongside simulation training to ensure comprehensive skill development.

Conclusion:

Advancements in XR and AI technologies are transforming the training landscape for ROP specialists, aiming to reduce childhood blindness through improved access to effective training while acknowledging the need to address existing limitations.