Artificial Cognition for Detection of Mental Disability: A Vision Transformer Approach for Alzheimer’s Disease

12Citations
Citations of this article
22Readers
Mendeley users who have this article in their library.

Abstract

Alzheimer’s disease is a common neurological disorder and mental disability that causes memory loss and cognitive decline, presenting a major challenge to public health due to its impact on millions of individuals worldwide. It is crucial to diagnose and treat Alzheimer’s in a timely manner to improve the quality of life of both patients and caregivers. In the recent past, machine learning techniques have showed potential in detecting Alzheimer’s disease by examining neuroimaging data, especially Magnetic Resonance Imaging (MRI). This research proposes an attention-based mechanism that employs the vision transformer approach to detect Alzheimer’s using MRI images. The presented technique applies preprocessing to the MRI images and forwards them to a vision transformer network for classification. This network is trained on the publicly available Kaggle dataset, and it illustrated impressive results with an accuracy of 99.06%, precision of 99.06%, recall of 99.14%, and F1-score of 99.1%. Furthermore, a comparative study is also conducted to evaluate the performance of the proposed method against various state-of-the-art techniques on diverse datasets. The proposed method demonstrated superior performance, outperforming other published methods when applied to the Kaggle dataset.

References Powered by Scopus

Automatic classification of MR scans in Alzheimer's disease

998Citations
N/AReaders
Get full text

Hybrid intelligent techniques for MRI brain images classification

485Citations
N/AReaders
Get full text

Random forest-based similarity measures for multi-modal classification of Alzheimer's disease

394Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Investigating Deep Learning for Early Detection and Decision-Making in Alzheimer’s Disease: A Comprehensive Review

6Citations
N/AReaders
Get full text

Computer-aided diagnosis of Alzheimer’s disease and neurocognitive disorders with multimodal Bi-Vision Transformer (BiViT)

4Citations
N/AReaders
Get full text

A Feature-Fusion Technique-Based Alzheimer’s Disease Classification Using Magnetic Resonance Imaging

2Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Almufareh, M. F., Tehsin, S., Humayun, M., & Kausar, S. (2023). Artificial Cognition for Detection of Mental Disability: A Vision Transformer Approach for Alzheimer’s Disease. Healthcare (Switzerland), 11(20). https://doi.org/10.3390/healthcare11202763

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 3

43%

Researcher 2

29%

Professor / Associate Prof. 1

14%

Lecturer / Post doc 1

14%

Readers' Discipline

Tooltip

Computer Science 5

83%

Mathematics 1

17%

Article Metrics

Tooltip
Mentions
Blog Mentions: 1
News Mentions: 2

Save time finding and organizing research with Mendeley

Sign up for free