Automated Detection and Classification of Oral Squamous Cell Carcinoma Using Deep Neural Networks

This work aims to classify normal and carcinogenic cells in the oral cavity using two different approaches with an eye towards achieving high accuracy. The first approach extracts local binary patterns and metrics derived from a histogram from the dataset and is fed to several machine-learning model...

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Detalles Bibliográficos
Autores principales: Ananthakrishnan, Balasundaram, Shaik, Ayesha, Kumar, Soham, Narendran, S. O., Mattu, Khushi, Kavitha, Muthu Subash
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10001077/
https://www.ncbi.nlm.nih.gov/pubmed/36900062
http://dx.doi.org/10.3390/diagnostics13050918

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10001077/
https://www.ncbi.nlm.nih.gov/pubmed/36900062
http://dx.doi.org/10.3390/diagnostics13050918

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