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Alzheimer’s disease diagnosis and classification using deep learning techniques

Alzheimer’s disease is an incurable neurodegenerative disease that affects brain memory mainly in aged people. Alzheimer’s disease occurs worldwide and mainly affects people aged older than 65 years. Early diagnosis for accurate detection is needed for this disease. Manual diagnosis by health specia...

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Autor principal: Al Shehri, Waleed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280208/
https://www.ncbi.nlm.nih.gov/pubmed/37346304
http://dx.doi.org/10.7717/peerj-cs.1177
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author Al Shehri, Waleed
author_facet Al Shehri, Waleed
author_sort Al Shehri, Waleed
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description Alzheimer’s disease is an incurable neurodegenerative disease that affects brain memory mainly in aged people. Alzheimer’s disease occurs worldwide and mainly affects people aged older than 65 years. Early diagnosis for accurate detection is needed for this disease. Manual diagnosis by health specialists is error prone and time consuming due to the large number of patients presenting with the disease. Various techniques have been applied to the diagnosis and classification of Alzheimer’s disease but there is a need for more accuracy in early diagnosis solutions. The model proposed in this research suggests a deep learning-based solution using DenseNet-169 and ResNet-50 CNN architectures for the diagnosis and classification of Alzheimer’s disease. The proposed model classifies Alzheimer’s disease into Non-Dementia, Very Mild Dementia, Mild Dementia, and Moderate Dementia. The DenseNet-169 architecture outperformed in the training and testing phases. The training and testing accuracy values for DenseNet-169 are 0.977 and 0.8382, while the accuracy values for ResNet-50 were 0.8870 and 0.8192. The proposed model is usable for real-time analysis and classification of Alzheimer’s disease.
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spelling pubmed-102802082023-06-21 Alzheimer’s disease diagnosis and classification using deep learning techniques Al Shehri, Waleed PeerJ Comput Sci Artificial Intelligence Alzheimer’s disease is an incurable neurodegenerative disease that affects brain memory mainly in aged people. Alzheimer’s disease occurs worldwide and mainly affects people aged older than 65 years. Early diagnosis for accurate detection is needed for this disease. Manual diagnosis by health specialists is error prone and time consuming due to the large number of patients presenting with the disease. Various techniques have been applied to the diagnosis and classification of Alzheimer’s disease but there is a need for more accuracy in early diagnosis solutions. The model proposed in this research suggests a deep learning-based solution using DenseNet-169 and ResNet-50 CNN architectures for the diagnosis and classification of Alzheimer’s disease. The proposed model classifies Alzheimer’s disease into Non-Dementia, Very Mild Dementia, Mild Dementia, and Moderate Dementia. The DenseNet-169 architecture outperformed in the training and testing phases. The training and testing accuracy values for DenseNet-169 are 0.977 and 0.8382, while the accuracy values for ResNet-50 were 0.8870 and 0.8192. The proposed model is usable for real-time analysis and classification of Alzheimer’s disease. PeerJ Inc. 2022-12-20 /pmc/articles/PMC10280208/ /pubmed/37346304 http://dx.doi.org/10.7717/peerj-cs.1177 Text en © 2022 Al Shehri https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited.
spellingShingle Artificial Intelligence
Al Shehri, Waleed
Alzheimer’s disease diagnosis and classification using deep learning techniques
title Alzheimer’s disease diagnosis and classification using deep learning techniques
title_full Alzheimer’s disease diagnosis and classification using deep learning techniques
title_fullStr Alzheimer’s disease diagnosis and classification using deep learning techniques
title_full_unstemmed Alzheimer’s disease diagnosis and classification using deep learning techniques
title_short Alzheimer’s disease diagnosis and classification using deep learning techniques
title_sort alzheimer’s disease diagnosis and classification using deep learning techniques
topic Artificial Intelligence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280208/
https://www.ncbi.nlm.nih.gov/pubmed/37346304
http://dx.doi.org/10.7717/peerj-cs.1177
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