The Use of Machine Learning to Support the Diagnosis of Oral Alterations

Objective: To verify the accuracy of deep learning models in detecting cellular alterations in histological images of oral mucosa. Material and Methods: The study compares three convolutional neural network (CNN) architectures for classifying histological images: EfficientNet-B3, MobileNet-V2, and...

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Bibliographic Details
Main Authors: Rosana Leal do Prado, Juliane Avansini Marsicano, Amanda Keren Frois, Jacques Duílio Brancher
Format: Article
Language:English
Published: Association of Support to Oral Health Research (APESB) 2025-01-01
Series:Pesquisa Brasileira em Odontopediatria e Clínica Integrada
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Online Access:https://revista.uepb.edu.br/PBOCI/article/view/4227
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