aceArtificial Intelligence-Assisted Reconstruction Planning of Cheek Soft Tissue Defects: A Comparative Study Against Surgical Expert Consensus
Background: Reconstructive planning for cheek soft tissue defects requires expert assessment of defect size and location to preserve aesthetic harmony. Artificial intelligence (AI), particularly large language models (LLMs), has emerged as a potential decision-support tool in plastic and reconstructive surgery. This study evaluates the accuracy and reliability of ChatGPT-4o in proposing reconstructive approaches for post-excisional cheek defects. Methods: A comparative observational image-based study was perform…
In a simulated image-based test, ChatGPT-4o's proposed cheek reconstruction plans earned high expert ratings for clinical accuracy and safety, suggesting a possible decision-support role for surgeons.
The test used simulated defects on healthy volunteers' photographs, ChatGPT-4o could not produce visual depictions of the proposed flaps, and prospective clinical validation is still needed.
Evidence
- Peer-reviewedAesthetic Plastic Surgery2026-10-20
How should this claim be treated?
Truvace Impact Record TRV-2026-2088, v1: “Artificial Intelligence-Assisted Reconstruction Planning of Cheek Soft Tissue Defects: A Comparative Study Against Surgical Expert Consensus.” Truvace, 2026-10-21. /record/TRV-2026-2088 (accessed at citation time). sha256 e1be88ea737d1ccc…
Calibration history
Every change to this record since certification, in the open. None yet — the reading has held since it entered the record.
Certified into the record
How to verify without trusting this page
Fetch the canonical text of any version from /api/record/TRV-2026-2088 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.