Ensemble-Based Alzheimer's Disease Classification Using Features Extracted from Hog Descriptor and Pre-trained Models

Nedim Muzoglu; Enver Akbacak

doi:10.35377/saucis...1493368

EN

Ensemble-Based Alzheimer's Disease Classification Using Features Extracted from Hog Descriptor and Pre-trained Models

Abstract

Alzheimer's Disease is the most common type of dementia and is a progressive, neurodegenerative disease. The disease worsens over time, and the patient becomes bedridden, unable to move or understand what is happening around him. The main concern of medicine is to slow down the progression of the disease for which no treatment has yet been developed. Artificial intelligence studies have achieved significant success in detecting many diseases. In this study, an artificial intelligence-based approach that uses MR images of the early stage of Alzheimer's Disease to detect the disease at an early stage is presented. Initially, a new dataset was created through the application of the fuzzy technique, thereby expanding the feature space. Then, an ensemble learning-based hybrid deep learning model was developed to reduce the misclassification rate for all classes. The features derived from the inception module, residual modules, and histogram of oriented gradients descriptor are subjected to classification through bagging and boosting algorithms. The proposed model has surpassed many state-of-the-art studies by achieving a high success rate of 99.60% in detecting Alzheimer's disease in its early stages.

Keywords

Ethical Statement

The study was prepared within the framework of ethical rules. Since the data set is open access, no additional ethical declaration was received.

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Details

Primary Language

English

Subjects

Software Testing, Verification and Validation , Software Engineering (Other)

Journal Section

Research Article

Authors

Nedim Muzoglu ^*
0000-0003-1591-2806
Türkiye

Enver Akbacak
0000-0002-6753-7887
Türkiye

Early Pub Date

December 23, 2024

Publication Date

December 31, 2024

Submission Date

May 31, 2024

Acceptance Date

September 30, 2024

Published in Issue

Year 2024 Volume: 7 Number: 3

DOI

https://doi.org/10.35377/saucis...1493368

IZ

https://izlik.org/JA43YL29DY

Cite

RIS / Bibtex

APA

Muzoglu, N., & Akbacak, E. (2024). Ensemble-Based Alzheimer’s Disease Classification Using Features Extracted from Hog Descriptor and Pre-trained Models. Sakarya University Journal of Computer and Information Sciences, 7(3), 416-426. https://doi.org/10.35377/saucis...1493368

AMA

1.Muzoglu N, Akbacak E. Ensemble-Based Alzheimer’s Disease Classification Using Features Extracted from Hog Descriptor and Pre-trained Models. SAUCIS. 2024;7(3):416-426. doi:10.35377/saucis.1493368

Chicago

Muzoglu, Nedim, and Enver Akbacak. 2024. “Ensemble-Based Alzheimer’s Disease Classification Using Features Extracted from Hog Descriptor and Pre-Trained Models”. Sakarya University Journal of Computer and Information Sciences 7 (3): 416-26. https://doi.org/10.35377/saucis. 1493368.

EndNote

Muzoglu N, Akbacak E (December 1, 2024) Ensemble-Based Alzheimer’s Disease Classification Using Features Extracted from Hog Descriptor and Pre-trained Models. Sakarya University Journal of Computer and Information Sciences 7 3 416–426.

IEEE

[1]N. Muzoglu and E. Akbacak, “Ensemble-Based Alzheimer’s Disease Classification Using Features Extracted from Hog Descriptor and Pre-trained Models”, SAUCIS, vol. 7, no. 3, pp. 416–426, Dec. 2024, doi: 10.35377/saucis...1493368.

ISNAD

Muzoglu, Nedim - Akbacak, Enver. “Ensemble-Based Alzheimer’s Disease Classification Using Features Extracted from Hog Descriptor and Pre-Trained Models”. Sakarya University Journal of Computer and Information Sciences 7/3 (December 1, 2024): 416-426. https://doi.org/10.35377/saucis. 1493368.

JAMA

1.Muzoglu N, Akbacak E. Ensemble-Based Alzheimer’s Disease Classification Using Features Extracted from Hog Descriptor and Pre-trained Models. SAUCIS. 2024;7:416–426.

MLA

Muzoglu, Nedim, and Enver Akbacak. “Ensemble-Based Alzheimer’s Disease Classification Using Features Extracted from Hog Descriptor and Pre-Trained Models”. Sakarya University Journal of Computer and Information Sciences, vol. 7, no. 3, Dec. 2024, pp. 416-2, doi:10.35377/saucis. 1493368.

Vancouver

1.Nedim Muzoglu, Enver Akbacak. Ensemble-Based Alzheimer’s Disease Classification Using Features Extracted from Hog Descriptor and Pre-trained Models. SAUCIS. 2024 Dec. 1;7(3):416-2. doi:10.35377/saucis. 1493368

Öz

Ensemble-Based Alzheimer's Disease Classification Using Features Extracted from Hog Descriptor and Pre-trained Models

Abstract

Keywords

Ethical Statement

References

Details

Primary Language

Subjects

Journal Section

Authors

Early Pub Date

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

Cite