UGC Approved Journal no 63975(19)

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

Volume 10 Issue 3
March-2023
eISSN: 2349-5162

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

7.95 impact factor calculated by Google scholar

Unique Identifier

Published Paper ID:
JETIRFV06040


Registration ID:
510509

Page Number

204-210

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Title

AUTOMATED DIAGNOSIS METHOD FOR ALZHEIMER’S DISEASE USING CEREBRAL CATHETER ANGIOGRAM NEUROIMAGING AND ALEXNET ARCHITECTUREIN DEEP LEARNING

Abstract

Alzheimer's disease (AD) is a neurological disorder that kills brain cells and causes memory loss in the patient. Early detection can protect the patient's brain cells from further damage and prevent irreversible memory loss. Several treatments focus on detecting the condition quickly, accurately, and early to limit the damage to a patient's mental health. Recently, various automated technologies and methods for diagnosing Alzheimer's disease have been introduced. Deep learning is a robust machine learning technique for classifying and extracting low-level to high-level features. We propose automated method for diagnosis Alzheimer's disease using Alex Net architecture and a convolutional neural network (CNN). This research aims to develop a helpful framework for the early identification of Alzheimer's disease using Magnetic Resonance Angiography (MRA) neuroimages.

Key Words

Alzheimer’s disease, neuroimaging, Deep Learning, Convolutional Neural Network (CNN), Alex net.

Cite This Article

"AUTOMATED DIAGNOSIS METHOD FOR ALZHEIMER’S DISEASE USING CEREBRAL CATHETER ANGIOGRAM NEUROIMAGING AND ALEXNET ARCHITECTUREIN DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 3, page no.204-210, March-2023, Available :http://www.jetir.org/papers/JETIRFV06040.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

"AUTOMATED DIAGNOSIS METHOD FOR ALZHEIMER’S DISEASE USING CEREBRAL CATHETER ANGIOGRAM NEUROIMAGING AND ALEXNET ARCHITECTUREIN DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 3, page no. pp204-210, March-2023, Available at : http://www.jetir.org/papers/JETIRFV06040.pdf

Publication Details

Published Paper ID: JETIRFV06040
Registration ID: 510509
Published In: Volume 10 | Issue 3 | Year March-2023
DOI (Digital Object Identifier):
Page No: 204-210
Country: -, -, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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