AI & Health · Research Report

Mixed Reality in Medical Training: Evidence Review

Reviewing the evidence on volumetric and mixed-reality communication for remote medical procedure training — what it can show, what it has shown, and what remains unproven.

Published 2025For Medical Educators & Health SystemsPublisher: FAIR Labs, Washington, DC
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Summary

What the evidence supports, and what it does not

Immersive simulation is a real and useful addition to the medical educator's toolkit, best understood as a maturing complement to—not a replacement for—cadaveric, bench, and supervised clinical training. The evidence most strongly supports its value for early procedural rehearsal, anatomical understanding, and repeatable deliberate practice, particularly where a learner can fail safely and often. The evidence is thinner, and should be read cautiously, for durable skill retention, transfer to live patients, and the newest frontier— volumetric telepresence for remote procedural mentoring—where enthusiasm currently outruns controlled data. This report maps that uneven landscape and proposes how to strengthen it.

Reviewing the evidence on volumetric and mixed-reality communication for remote medical procedure training — what it can show, what it has shown, and what remains unproven.

How to cite this report

Mixed Reality in Medical Training: Evidence Review. FAIR Labs Research Report. Fair Artificial Intelligence Research Labs, 2025. Available at https://fairlabs.ai/research/mixed-reality-medical-training

FAIR Labs (Fair Artificial Intelligence Research Labs) is a nonpartisan 501(c)(3) research institute in Washington, DC. Its reports may be reproduced with attribution for non-commercial purposes. For interviews, briefings or data requests, use the contact form.

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