This paper is in the following e-collection/theme issue:

#xGeriatricMedicine (3) Clinical Information and Decision Making (1966) Computer-Aided Diagnosis (263) Machine Learning (2138) Dementia and Cognitive Decline (715) Advancements in Neuroimaging (17)

Published on in Vol 6 (2025)

Preprints (earlier versions) of this paper are available at https://arxiv.org/abs/2405.09553v1, first published .
Improved Alzheimer Disease Diagnosis With a Machine Learning Approach and Neuroimaging: Case Study Development

Improved Alzheimer Disease Diagnosis With a Machine Learning Approach and Neuroimaging: Case Study Development

Improved Alzheimer Disease Diagnosis With a Machine Learning Approach and Neuroimaging: Case Study Development

Authors of this article:

Lilia Lazli1 Author Orcid Image
Article Authors Cited by (6) Tweetations (2) Metrics

Journals

  1. Erdoğmuş P, Kabakuş A. Early diagnosis of Alzheimer’s Disease using hybrid CNN-Transformer models with Grad-CAM interpretability. Gümüşhane Üniversitesi Fen Bilimleri Enstitüsü Dergisi 2025;15(3):829 View
  2. Yadav A, Khan I, Agarwal P, Kaur H. A proposed hybrid PCA–t-SNE approach for early prediction of Alzheimer’s disease. International Journal of Information Technology 2025;17(9):5231 View
  3. Sharma R, Acharya V. Lightweight Vision Transformer with transfer learning for interpretable Alzheimer’s disease severity assessment. Scientific Reports 2025;15(1) View
  4. Boudi A, He J, Abd El Kader I, Liu X, Mouhafid M. Advancing Alzheimer's Disease Diagnosis Using VGG19 and XGBoost: A Neuroimaging-Based Method. Current Alzheimer Research 2025;22(10):757 View
  5. Yu Z, Mulholland A, Huang T, Liu Q. Multimodal AI for Alzheimer’s Disease Diagnosis: A Systematic Review of Datasets, Models and Modalities (Preprint). Journal of Medical Internet Research 2025 View

Conference Proceedings

  1. Mohammed S, Malhotra N, Kumar S. 2025 5th Asian Conference on Innovation in Technology (ASIANCON). Dual-Model Framework for Alzheimer's Detection in CT Imaging: A Comparative Study of EfficientNetV2-B0 and ResNet50V2 View