The DenseNet121 and faster R-CNN algorithm were proved to offer the acceptable potential for classification and detection of cancerous lesions in oral photographic images.

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Cite This Study

Warin et al. (Fri,) studied this question.

synapsesocial.com/papers/69d9883c00ab073a27836e15 https://doi.org/https://doi.org/10.1111/jop.13227

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Automatic classification and detection of oral cancer in photographic images using deep learning algorithms | Synapse

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

12020 IEEE International Conference on Big Data (Big Data)2020 · 663 citations
2A deep learning nomogram kit for predicting metastatic lymph nodes in rectal cancer2020 · 30 citations
3Densely Connected Convolutional Networks2017 · 44,784 citations
4Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries2021 · 112,808 citations
5Current concepts in management of oral cancer – Surgery2008 · 810 citations