ArticleBrain informatics2023
Four-way classification of Alzheimer's disease using deep Siamese convolutional neural network with triplet-loss function.
Article in Brain informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- X-ViTCNN: A Novel Network-Level Fusion of Transfer Learning and Customized Vision Transformer for Multi-Stage Alzheimer's Disease Prediction Using MRI Scans.Diagnostics (Basel, Switzerland) · 2026Article
- Multimodal fusion and explainability of artificial intelligence models in Alzheimer's Disease detection.Brain informatics · 2026Review
- Advances in AI-based diagnosis of Alzheimer's disease using MRI: a comprehensive survey.Frontiers in medicine · 2026Review
- Integrating anatomical priors and clinical semantics for MRI-based diagnosis and care support in Alzheimer's disease.Frontiers in neuroscience · 2026Article
- Alzheimer's disease detection from structural brain MRI using FFA U-Net segmentation and transfer learning.Frontiers in neuroscience · 2026Article
- Advancing Alzheimer's disease detection: a novel convolutional neural network based framework leveraging EEG data and segment length analysis.Brain informatics · 2025Article
- A Convolutional Mixer-Based Deep Learning Network for Alzheimer's Disease Classification from Structural Magnetic Resonance Imaging.Diagnostics (Basel, Switzerland) · 2025Article
- Recent Advancements in Neuroimaging-Based Alzheimer's Disease Prediction Using Deep Learning Approaches in e-Health: A Systematic Review.Health science reports · 2025Review
- Synthesizing network pharmacology, bioinformatics, and in vitro experimental verification to screen candidate targets of Salidroside for mitigating Alzheimer's disease.Naunyn-Schmiedeberg's archives of pharmacology · 2025Article
- Article
- Fractional gradient optimized explainable convolutional neural network for Alzheimer's disease diagnosis.Heliyon · 2024Article
- Interpreting artificial intelligence models: a systematic review on the application of LIME and SHAP in Alzheimer's disease detection.Brain informatics · 2024Review
- An Explainable AI Paradigm for Alzheimer's Diagnosis Using Deep Transfer Learning.Diagnostics (Basel, Switzerland) · 2024Article
- DenseIncepS115: a novel network-level fusion framework for Alzheimer's disease prediction using MRI images.Frontiers in oncology · 2024Article
- Improving Alzheimer's Disease Classification in Brain MRI Images Using a Neural Network Model Enhanced with PCA and SWLDA.Healthcare (Basel, Switzerland) · 2023Article
- A systematic review on machine learning and deep learning techniques in the effective diagnosis of Alzheimer's disease.Brain informatics · 2023Article
- Four-way classification of Alzheimer's disease using deep Siamese convolutional neural network with triplet-loss function.Brain informatics · 2023Article
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Authors and funding
8 authors.
Funding
Abstract
Alzheimer's disease (AD) is a neurodegenerative disease that causes irreversible damage to several brain regions, including the hippocampus causing impairment in cognition, function, and behaviour. Early diagnosis of the disease will reduce the suffering of the patients and their family members. Towards this aim, in this paper, we propose a Siamese Convolutional Neural Network (SCNN) architecture that employs the triplet-loss function for the representation of input MRI images as k-dimensional embeddings. We used both pre-trained and non-pretrained CNNs to transform images into the embedding space. These embeddings are subsequently used for the 4-way classification of Alzheimer's disease. The model efficacy was tested using the ADNI and OASIS datasets which produced an accuracy of 91.83% and 93.85%, respectively. Furthermore, obtained results are compared with similar methods proposed in the literature.
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