UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 10 Issue 1
January-2023
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2301254


Registration ID:
507279

Page Number

c425-c428

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Title

A CNN Deep Learning Technique for Prediction of Lung Cancer Diseases

Abstract

Timely diagnosis and determination to the type of lung cancer diseases has important clinical significance. Generally, it requires multiple imaging methods to complement each other to obtain a comprehensive diagnosis. Various learning methods, such as conventional clustering and classification, have been applied in diagnosing diseases to categorize samples based on their features. Artificial intelligence based machine learning techniques provides accurate prediction model of the various biomedical diseases. This paper presents CNN deep learning technique for prediction of lung cancer diseases.

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"A CNN Deep Learning Technique for Prediction of Lung Cancer Diseases", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 1, page no.c425-c428, January-2023, Available :http://www.jetir.org/papers/JETIR2301254.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"A CNN Deep Learning Technique for Prediction of Lung Cancer Diseases", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 1, page no. ppc425-c428, January-2023, Available at : http://www.jetir.org/papers/JETIR2301254.pdf

Publication Details

Published Paper ID: JETIR2301254
Registration ID: 507279
Published In: Volume 10 | Issue 1 | Year January-2023
DOI (Digital Object Identifier):
Page No: c425-c428
Country: Bhopal, MP, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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