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A Recognition System for Diagnosing Salivary Gland Neoplasms Based on Vision Transformer.

Am J Pathol

February 2025

State Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, China. Electronic address:

Salivary gland neoplasms (SGNs) represent a group of human neoplasms characterized by a remarkable cytomorphologic diversity, which frequently poses diagnostic challenges. Accurate histologic categorization of salivary gland tumors is crucial to make precise diagnoses and guide decisions regarding patient management. Within the scope of this study, a computer-aided diagnosis model using Vision Transformer (ViT), a cutting-edge deep learning model in computer vision, was developed to accurately classify the most prevalent subtypes of SGNs.

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