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Page 423 Talwar et al. Art Int Surg. 2025;5:418-24 https://dx.doi.org/10.20517/ais.2025.22

Improving dataset diversity is critical to mitigating bias and ensuring AI models function well across diverse
patient populations. Additionally, addressing the computational burden and accessibility challenges of AI
deployment in VHR is necessary for widespread adoption. Future research should explore lightweight AI
models optimized for efficiency, leveraging techniques such as quantization to reduce computational
demands . Additionally, cloud-based AI solutions could expand access to AI-powered medical imaging in
[27]
[28]
resource-poor settings .
CONCLUSION
AI-powered medical imaging has shown potential for enhancing preoperative planning, intraoperative
decision making, and postoperative monitoring for VHR. Through advanced imaging techniques, AI tools
can predict complications, optimize surgical planning, and support long-term patient care. The studies in
this manuscript highlight the transformative impact of AI on VHR by addressing clinical challenges and
personalizing patient management.

However, several limitations must be addressed to realize the benefit of AI in VHR. Across applications,
models have struggled with misclassification and decreased precision in rare outcomes. Additionally, the
risk of overdiagnosis, particularly in low-prevalence complications, underscores the importance of ongoing
validation in real-world settings. Future work should focus on developing large, diverse datasets, improving
model interpretability, and developing scalable solutions.

While AI-powered medical imaging in VHR is in its early stages, its progress is promising. With efforts to
refine AI systems, the future of VHR holds the potential to improve surgical outcomes, tailor care to
individual needs, and bridge technology with compassionate care. These advancements promise to
transform both VHR and the broader field of surgical innovation.

DECLARATIONS
Authors’ contributions
Made substantial contributions to the conception and design of the review: Talwar A, Kelshiker AI, Fischer
JP

Availability of data and materials
Not applicable.

Financial support and sponsorship
None.

Conflicts of interest
All authors declared that there are no conflicts of interest.

Ethical approval and consent to participate
Not applicable.

Consent for publication
Not applicable.

Copyright
© The Author(s) 2025.