Effectiveness of deep learning classifiers in histopathological diagnosis of oral squamous cell carcinoma by pathologists

Effectiveness of deep learning classifiers in histopathological diagnosis of oral squamous cell carcinoma by pathologists

Abstract The study aims to identify histological classifiers from histopathological images of oral squamous cell carcinoma using convolutional neural network (CNN) deep learning models and shows how the results can improve diagnosis. Histopathological samples of oral squamous cell carcinoma were pre...

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Bibliographic Details
Main Authors: Shintaro Sukegawa, Sawako Ono, Futa Tanaka, Yuta Inoue, Takeshi Hara, Kazumasa Yoshii, Keisuke Nakano, Kiyofumi Takabatake, Hotaka Kawai, Shimada Katsumitsu, Fumi Nakai, Yasuhiro Nakai, Ryo Miyazaki, Satoshi Murakami, Hitoshi Nagatsuka, Minoru Miyake
Format: Article
Language:English
Published: Nature Portfolio 2023-07-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-38343-y

Internet

https://doi.org/10.1038/s41598-023-38343-y

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