aceOne-shot synthesis of rare gastrointestinal lesions improves diagnostic accuracy and clinical training
Abstract Rare gastrointestinal lesions are infrequently encountered in routine endoscopy, limiting data for developing reliable artificial intelligence (AI) models and training novice clinicians. Here we present EndoRare, a one-shot, retraining-free generative framework that synthesizes diverse lesion exemplars from a single reference image. Using language-guided concept disentanglement, EndoRare separates pathognomonic lesion features from non-diagnostic attributes, encoding the former into a learnable prototyp…
Synthetic images made from one reference photo were judged clinically plausible by experts, and adding them to training data raised AI detection rates for four rare gut conditions at low false-positive rates.
The reader study was exploratory and showed only an association, and the authors say prospective controlled validation is still needed.
Evidence
- Peer-reviewedNature Communications2026-10-25
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Truvace Impact Record TRV-2026-2284, v1: “One-shot synthesis of rare gastrointestinal lesions improves diagnostic accuracy and clinical training.” Truvace, 2026-10-27. /record/TRV-2026-2284 (accessed at citation time). sha256 157315930e90d71c…
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