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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15

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Paper Title:	Lung Cancer Detection Using Artificial Intelligence
Authors Name:	Wagh Nishigandha , Beldar Sonali , Arkhade Prajakta , Wagh Shobha
Unique Id:	IJSDR2201048
Published In:	Volume 7 Issue 1, January-2022
Abstract:	Identification of lung cancer is an efficient way to minimize the death rate and maximize survival rate of patients. It is an essential step to screen out the computed tomography (CT) images for pulmonary nodules towards the efficient treatment of lung cancer. However, robust nodule identification and detection is a most critical task due the complexity of the surrounding environment and heterogeneity of the lung nodules. The use of machine learning to detect, predict, and classify disease has grown exponentially in the past few years, especially for complex tasks such as lung cancer detection and recognition. Deep Convolutional neural networks (DCNN) have exploded in popularity for transforming the field of computer vision research. In this paper, we are using Deep Convolutional Neural Network for lung cancer classification using CT images-based lung cancer image dataset consortium (LIDC) for detecting cancerous and noncancerous lung nodules for measuring the accuracy of classification better than existing methods.
Keywords:	Lung Cancer, CNN, Computed Tomography, computer vision.
Cite Article:	"Lung Cancer Detection Using Artificial Intelligence", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 1, page no.315 - 316, January-2022, Available :http://www.ijsdr.org/papers/IJSDR2201048.pdf
Downloads:	000337070
Publication Details:	Published Paper ID: IJSDR2201048 Registration ID:193883 Published In: Volume 7 Issue 1, January-2022 DOI (Digital Object Identifier): Page No: 315 - 316 Publisher: IJSDR \| www.ijsdr.org ISSN Number: 2455-2631

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