A Comparative Analysis on Metaheuristic Algorithms Based Vision Transformer Model for Early Detection of Alzheimer's Disease
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Abstract (arXiv)
A number of life threatening neuro-degenerative disorders had degraded the quality of life for the older generation in particular. Dementia is one such symptom which may lead to a severe condition called Alzheimer's disease if not detected at an early stage. It has been reported that the progression of such disease from a normal stage is due to the change in several parameters inside the human brain. In this paper, an innovative metaheuristic algorithms based ViT model has been proposed for the identification of dementia at different stage. A sizeable number of test data have been utilized for the validation of the proposed scheme. It has also been demonstrated that our model exhibits superior performance in terms of accuracy, precision, recall as well as F1-score.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 6 of its 24 references that are in the map. First posted on arXiv 18 Jan 2024.
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6 of 24 references.
References · 6
- 2017Attention Is All You Needcited by 59,932
- 2015Deep Residual Learning for Image Recognitioncited by 51,809
- 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
- 2016Layer Normalizationcited by 5,579
- 2017Residual and Plain Convolutional Neural Networks for 3D Brain MRI Classificationcited by 47
- 2019Diagnosis of Alzheimer's Disease via Multi-modality 3D Convolutional Neural Networkcited by 15
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