Recognition and diagnosis of Alzheimer’s Disease using T1-weighted magnetic resonance imaging via integrating CNN and Swin vision transformer

The stated high accuracy indicates that the suggested vision transformer model has the capacity to assist healthcare providers and researchers in generating well-informed and precise evaluations of individuals with Alzheimer's disease.

Authors

Institutions

Publication Details

Journal
Clinics
Published
2025-01-01
DOI
https://doi.org/10.1016/j.clinsp.2025.100673
Citations
3
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
2.53
Controls
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article

Recognition and diagnosis of Alzheimer’s Disease using T1-weighted magnetic resonance imaging via integrating CNN and Swin vision transformer

Hui Sheng, Yanlei Wang, Xueling Wang
3 citations
Clinics
Brain Tumor Detection and Classification
2.53
article

Recognition and diagnosis of Alzheimer’s Disease using T1-weighted magnetic resonance imaging via integrating CNN and Swin vision transformer

Hui Sheng, Yanlei Wang, Xueling Wang
article en
3 citations

Abstract

The stated high accuracy indicates that the suggested vision transformer model has the capacity to assist healthcare providers and researchers in generating well-informed and precise evaluations of individuals with Alzheimer's disease.

ClinicsVol. 80
Shandong University (CN), Shandong University of Political Science and Law (CN), Yantaishan Hospital (CN)
Openalex Percentile: Top 10%
Brain Tumor Detection and Classification
2.53
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