IJNRD Research Journal

WhatsApp
Click Here

WhatsApp editor@ijnrd.org
IJNRD
INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)

Call For Paper

For Authors

Forms / Download

Published Issue Details

Editorial Board

Other IMP Links

Facts & Figure

Impact Factor : 8.76

Issue per Year : 12

Volume Published : 9

Issue Published : 96

Article Submitted :

Article Published :

Total Authors :

Total Reviewer :

Total Countries :

Indexing Partner

Join RMS/Earn 300

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Published Paper Details
Paper Title: Oral Cancer Classification using EfficientNet
Authors Name: Vasu Rastogi , Ajay Pal Singh , Ritik Kumar Kharwar , Rishabh Nagar
Download E-Certificate: Download
Author Reg. ID:
IJNRD_209460
Published Paper Id: IJNRD2311269
Published In: Volume 8 Issue 11, November-2023
DOI:
Abstract: Oral cancer is a common and potentially fatal condition, early and correct detection is essential for successful treatment. This study investigates the use of histopathologic images to classify oral cancer using Google's EfficientNet Convolutional Neural Network (CNN) architecture. The work makes use of a dataset made up of several histological samples of oral cancer to create a robust and accurate classification model. Our findings show that the EfficientNet CNN is highly accurate in differentiating between different subtypes of oral cancer. In addition, we compare the proposed model's performance to other categorization techniques, demonstrating its superiority. This study offers a trustworthy and automated method to assist medical practitioners in early detection, potentially improving patient outcomes and representing a substantial advancement in the field of mouth cancer diagnostics.
Keywords: Oral Cancer Classification, Histopathologic Images, Machine Learning, EfficientNet Model, Oral squamous cell carcinoma (OSCC)
Cite Article: "Oral Cancer Classification using EfficientNet", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 11, page no.c566-c572, November-2023, Available :http://www.ijnrd.org/papers/IJNRD2311269.pdf
Downloads: 000118766
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID:IJNRD2311269
Registration ID: 209460
Published In: Volume 8 Issue 11, November-2023
DOI (Digital Object Identifier):
Page No: c566-c572
Country: Gharuan, SAS nagar Mohali, Punjab, India
Research Area: Computer Science & Technology 
Publisher : IJ Publication
Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2311269
Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2311269
Share Article:
Share

Click Here to Download This Article

Article Preview
Click Here to Download This Article

Major Indexing from www.ijnrd.org
Semantic Scholar Microsaoft Academic ORCID Zenodo
Google Scholar ResearcherID Thomson Reuters Mendeley : reference manager Academia.edu
arXiv.org : cornell university library Research Gate CiteSeerX PUBLON
DRJI SSRN Scribd DocStoc

ISSN Details

ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016

DOI (A digital object identifier)


Providing A digital object identifier by DOI
How to Get DOI? DOI

Conference

Open Access License Policy

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Creative Commons License This material is Open Knowledge This material is Open Data This material is Open Content

Important Details

Social Media

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Join RMS/Earn 300

IJNRD