Multi-Method Analysis of Medical Records and MRI Images for Early Diagnosis of Dementia and Alzheimer’s Disease Based on Deep Learning and Hybrid Methods

Dementia and Alzheimer’s disease are caused by neurodegeneration and poor communication between neurons in the brain. So far, no effective medications have been discovered for dementia and Alzheimer’s disease. Thus, early diagnosis is necessary to avoid the development of these diseases. In this stu...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Badiea Abdulkarem Mohammed, Ebrahim Mohammed Senan, Taha H. Rassem, Nasrin M. Makbol, Adwan Alownie Alanazi, Zeyad Ghaleb Al-Mekhlafi, Tariq S. Almurayziq, Fuad A. Ghaleb
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	Alzheimer dementia t-SNE algorithm machine learning deep learning hybrid techniques Electronics TK7800-8360
Acceso en línea:	https://doaj.org/article/2502dcac4a47464788e01fe8dc0d1749
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:2502dcac4a47464788e01fe8dc0d1749
record_format	dspace
spelling	oai:doaj.org-article:2502dcac4a47464788e01fe8dc0d17492021-11-25T17:25:24ZMulti-Method Analysis of Medical Records and MRI Images for Early Diagnosis of Dementia and Alzheimer’s Disease Based on Deep Learning and Hybrid Methods10.3390/electronics102228602079-9292https://doaj.org/article/2502dcac4a47464788e01fe8dc0d17492021-11-01T00:00:00Zhttps://www.mdpi.com/2079-9292/10/22/2860https://doaj.org/toc/2079-9292Dementia and Alzheimer’s disease are caused by neurodegeneration and poor communication between neurons in the brain. So far, no effective medications have been discovered for dementia and Alzheimer’s disease. Thus, early diagnosis is necessary to avoid the development of these diseases. In this study, efficient machine learning algorithms were assessed to evaluate the Open Access Series of Imaging Studies (OASIS) dataset for dementia diagnosis. Two CNN models (AlexNet and ResNet-50) and hybrid techniques between deep learning and machine learning (AlexNet+SVM and ResNet-50+SVM) were also evaluated for the diagnosis of Alzheimer’s disease. For the OASIS dataset, we balanced the dataset, replaced the missing values, and applied the t-Distributed Stochastic Neighbour Embedding algorithm (t-SNE) to represent the high-dimensional data in the low-dimensional space. All of the machine learning algorithms, namely, Support Vector Machine (SVM), Decision Tree, Random Forest and K Nearest Neighbours (KNN), achieved high performance for diagnosing dementia. The random forest algorithm achieved an overall accuracy of 94% and precision, recall and F1 scores of 93%, 98% and 96%, respectively. The second dataset, the MRI image dataset, was evaluated by AlexNet and ResNet-50 models and AlexNet+SVM and ResNet-50+SVM hybrid techniques. All models achieved high performance, but the performance of the hybrid methods between deep learning and machine learning was better than that of the deep learning models. The AlexNet+SVM hybrid model achieved accuracy, sensitivity, specificity and AUC scores of 94.8%, 93%, 97.75% and 99.70%, respectively.Badiea Abdulkarem MohammedEbrahim Mohammed SenanTaha H. RassemNasrin M. MakbolAdwan Alownie AlanaziZeyad Ghaleb Al-MekhlafiTariq S. AlmurayziqFuad A. GhalebMDPI AGarticleAlzheimerdementiat-SNE algorithmmachine learningdeep learninghybrid techniquesElectronicsTK7800-8360ENElectronics, Vol 10, Iss 2860, p 2860 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Alzheimer dementia t-SNE algorithm machine learning deep learning hybrid techniques Electronics TK7800-8360
spellingShingle	Alzheimer dementia t-SNE algorithm machine learning deep learning hybrid techniques Electronics TK7800-8360 Badiea Abdulkarem Mohammed Ebrahim Mohammed Senan Taha H. Rassem Nasrin M. Makbol Adwan Alownie Alanazi Zeyad Ghaleb Al-Mekhlafi Tariq S. Almurayziq Fuad A. Ghaleb Multi-Method Analysis of Medical Records and MRI Images for Early Diagnosis of Dementia and Alzheimer’s Disease Based on Deep Learning and Hybrid Methods
description	Dementia and Alzheimer’s disease are caused by neurodegeneration and poor communication between neurons in the brain. So far, no effective medications have been discovered for dementia and Alzheimer’s disease. Thus, early diagnosis is necessary to avoid the development of these diseases. In this study, efficient machine learning algorithms were assessed to evaluate the Open Access Series of Imaging Studies (OASIS) dataset for dementia diagnosis. Two CNN models (AlexNet and ResNet-50) and hybrid techniques between deep learning and machine learning (AlexNet+SVM and ResNet-50+SVM) were also evaluated for the diagnosis of Alzheimer’s disease. For the OASIS dataset, we balanced the dataset, replaced the missing values, and applied the t-Distributed Stochastic Neighbour Embedding algorithm (t-SNE) to represent the high-dimensional data in the low-dimensional space. All of the machine learning algorithms, namely, Support Vector Machine (SVM), Decision Tree, Random Forest and K Nearest Neighbours (KNN), achieved high performance for diagnosing dementia. The random forest algorithm achieved an overall accuracy of 94% and precision, recall and F1 scores of 93%, 98% and 96%, respectively. The second dataset, the MRI image dataset, was evaluated by AlexNet and ResNet-50 models and AlexNet+SVM and ResNet-50+SVM hybrid techniques. All models achieved high performance, but the performance of the hybrid methods between deep learning and machine learning was better than that of the deep learning models. The AlexNet+SVM hybrid model achieved accuracy, sensitivity, specificity and AUC scores of 94.8%, 93%, 97.75% and 99.70%, respectively.
format	article
author	Badiea Abdulkarem Mohammed Ebrahim Mohammed Senan Taha H. Rassem Nasrin M. Makbol Adwan Alownie Alanazi Zeyad Ghaleb Al-Mekhlafi Tariq S. Almurayziq Fuad A. Ghaleb
author_facet	Badiea Abdulkarem Mohammed Ebrahim Mohammed Senan Taha H. Rassem Nasrin M. Makbol Adwan Alownie Alanazi Zeyad Ghaleb Al-Mekhlafi Tariq S. Almurayziq Fuad A. Ghaleb
author_sort	Badiea Abdulkarem Mohammed
title	Multi-Method Analysis of Medical Records and MRI Images for Early Diagnosis of Dementia and Alzheimer’s Disease Based on Deep Learning and Hybrid Methods
title_short	Multi-Method Analysis of Medical Records and MRI Images for Early Diagnosis of Dementia and Alzheimer’s Disease Based on Deep Learning and Hybrid Methods
title_full	Multi-Method Analysis of Medical Records and MRI Images for Early Diagnosis of Dementia and Alzheimer’s Disease Based on Deep Learning and Hybrid Methods
title_fullStr	Multi-Method Analysis of Medical Records and MRI Images for Early Diagnosis of Dementia and Alzheimer’s Disease Based on Deep Learning and Hybrid Methods
title_full_unstemmed	Multi-Method Analysis of Medical Records and MRI Images for Early Diagnosis of Dementia and Alzheimer’s Disease Based on Deep Learning and Hybrid Methods
title_sort	multi-method analysis of medical records and mri images for early diagnosis of dementia and alzheimer’s disease based on deep learning and hybrid methods
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/2502dcac4a47464788e01fe8dc0d1749
work_keys_str_mv	AT badieaabdulkaremmohammed multimethodanalysisofmedicalrecordsandmriimagesforearlydiagnosisofdementiaandalzheimersdiseasebasedondeeplearningandhybridmethods AT ebrahimmohammedsenan multimethodanalysisofmedicalrecordsandmriimagesforearlydiagnosisofdementiaandalzheimersdiseasebasedondeeplearningandhybridmethods AT tahahrassem multimethodanalysisofmedicalrecordsandmriimagesforearlydiagnosisofdementiaandalzheimersdiseasebasedondeeplearningandhybridmethods AT nasrinmmakbol multimethodanalysisofmedicalrecordsandmriimagesforearlydiagnosisofdementiaandalzheimersdiseasebasedondeeplearningandhybridmethods AT adwanalowniealanazi multimethodanalysisofmedicalrecordsandmriimagesforearlydiagnosisofdementiaandalzheimersdiseasebasedondeeplearningandhybridmethods AT zeyadghalebalmekhlafi multimethodanalysisofmedicalrecordsandmriimagesforearlydiagnosisofdementiaandalzheimersdiseasebasedondeeplearningandhybridmethods AT tariqsalmurayziq multimethodanalysisofmedicalrecordsandmriimagesforearlydiagnosisofdementiaandalzheimersdiseasebasedondeeplearningandhybridmethods AT fuadaghaleb multimethodanalysisofmedicalrecordsandmriimagesforearlydiagnosisofdementiaandalzheimersdiseasebasedondeeplearningandhybridmethods
_version_	1718412337812078592

Multi-Method Analysis of Medical Records and MRI Images for Early Diagnosis of Dementia and Alzheimer’s Disease Based on Deep Learning and Hybrid Methods

Ejemplares similares