Industry 4.0 transformation: adaptive coati deep convolutional neural network-based oral cancer diagnosis in histopathological images for clinical applications-Reference-Cited by-同舟云学术

Industry 4.0 transformation: adaptive coati deep convolutional neural network-based oral cancer diagnosis in histopathological images for clinical applications

Published:2023-12-14 Issue:2 Volume:56 Page:
ISSN:0306-8919
Container-title:Optical and Quantum Electronics
language:en
Short-container-title:Opt Quant Electron

Author:

Dharani R.,Revathy S.

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials

Link

https://link.springer.com/content/pdf/10.1007/s11082-023-05716-6.pdf

Reference31 articles.

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2. Amin, I., Zamir, H., Khan, F. F.: Histopathological image analysis for oral squamous cell carcinoma classification using concatenated deep learning models. medRxiv. (2021) http://medrxiv.org/content/early/2021/05/14/2021.05.06.21256741. Abstract

3. Anwar, N., Pervez, S., Chundriger, Q., Awan, S., Moatter, T., Ali, T.S.: Oral cancer: clinicopathological features and associated risk factors in a high-risk population presenting to a major tertiary care center in Pakistan. PLoS ONE 15(8), e0236359 (2020)

4. Available online: https://www.kaggle.com/ashenafifasilkebede/dataset?select=val Accessed on 5 Jan 2023.

5. Chakraborty, D., Natarajan, C., Mukherjee, A.: Advances in oral cancer detection. Adv. Clin. Chem. 91, 181–200 (2019)

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