Seeing Beyond the Microscope: Artificial Intelligence and Fluorescence Confocal Digital Imaging in Pediatric Surgical Pathology.

ABSTRACT: Background: Digital pathology (DP) combined with fluorescence confocal microscopy (FCM) allows rapid tissue assessment while preserving specimens. Artificial intelligence (AI) and large language models (LLMs) may enhance diagnostic workflows, but their role in pediatric surgical pathology is largely unexplored. Methods: We conducted a prospective, single-center study including 20 pediatric surgical cases with ex vivo FCM images acquired intraoperatively. Two commercially available LLMs, GPT-4V (AnPathology-Gpt) and Claude 3.7 Sonnet (AnPathology Project), were tested using structured prompts to generate diagnostic reports with and without immunohistochemistry (IHC) data, when available. Outputs were compared against the gold standard diagnosis by an experienced pediatric path

SUBMITTER: Di Fabrizio D 

PROVIDER: S-EPMC12731743 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature