Oral mucosal lesions triage via YOLOv7 models

Oral mucosal lesions triage via YOLOv7 models

Background/purpose: The global incidence of lip and oral cavity cancer continues to rise, necessitating improved early detection methods. This study leverages the capabilities of computer vision and deep learning to enhance the early detection and classification of oral mucosal lesions. Methods: A d...

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Bibliographic Details
Main Authors: Yu Hsu, Cheng-Ying Chou, Yu-Cheng Huang, Yu-Chieh Liu, Yong-Long Lin, Zi-Ping Zhong, Jun-Kai Liao, Jun-Ching Lee, Hsin-Yu Chen, Jang-Jaer Lee, Shyh-Jye Chen
Format: Article
Language:English
Published: Elsevier 2025-07-01
Series:Journal of the Formosan Medical Association
Subjects:
Mouth neoplasms
Oral pathology
Deep learning
Artificial intelligence
Computer assisted decision making
Online Access:http://www.sciencedirect.com/science/article/pii/S0929664624003139
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http://www.sciencedirect.com/science/article/pii/S0929664624003139

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