ArticlePloS one2020
Alzheimer's disease diagnosis from diffusion tensor images using convolutional neural networks.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 4 of them syntheses that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
25 citing papers in PubMed, 4 syntheses or guidelines pooled it, 95 citations in OpenAlex.
- Predictive modelling of brain disorders with magnetic resonance imaging: A systematic review of modelling practices, transparency, and interpretability in the use of convolutional neural networks.Human brain mapping · 2023Pooled it
- Diagnostic Performance of Generative Adversarial Network-Based Deep Learning Methods for Alzheimer's Disease: A Systematic Review and Meta-Analysis.Frontiers in aging neuroscience · 2022Pooled it
- An Exploration: Alzheimer's Disease Classification Based on Convolutional Neural Network.BioMed research international · 2022Pooled it
- [Research on the application of convolution neural network in the diagnosis of Alzheimer's disease].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2021Pooled it
- Corpus callosum fractional anisotropy from routine diffusion tensor imaging predicts dementia in older adults beyond clinical risk factors.GeroScience · 2026Article
- Early Alzheimer's risk detection via diffusion tensor imaging using a few-shot multichannel attention residual learning network.Frontiers in artificial intelligence · 2026Article
- The application progress of artificial intelligence in the diagnosis of Alzheimer's disease.Frontiers in neurology · 2026Review
- Enhancing Early Diagnosis: Multimodal AI Approaches for Neurodegenerative Diseases.Journal of biotechnology and biomedicine · 2026Article
- White matter trajectories in Down syndrome and Alzheimer's disease: Insights from diffusion tensor-based morphometry.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Comparison of machine learning algorithms for automatic prediction of Alzheimer disease.Journal of the Chinese Medical Association : JCMA · 2025Article
- AlzheimerViT: harnessing lightweight vision transformer architecture for proactive Alzheimer's screening.Frontiers in medicine · 2025Article
- Hybrid-RViT: Hybridizing ResNet-50 and Vision Transformer for Enhanced Alzheimer's disease detection.PloS one · 2025Article
- Effective deep convolutional neural network with attention mechanism for Alzheimer disease classification.Frontiers in radiology · 2025Article
- Synergistic associations of CD33 variants and hypertension with brain and cognitive aging among dementia-free older adults: A population-based study.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Understanding machine learning applications in dementia research and clinical practice: a review for biomedical scientists and clinicians.Alzheimer's research & therapy · 2024Review
- Article
- Detection of mild cognitive impairment based on attention mechanism and parallel dilated convolution.PeerJ. Computer science · 2024Article
- Can T1-Weighted Magnetic Resonance Imaging Significantly Improve Mini-Mental State Examination-Based Distinguishing Between Mild Cognitive Impairment and Early-Stage Alzheimer's Disease?Journal of Alzheimer's disease : JAD · 2023Article
- Prediction of Alzheimer's Disease by a Novel Image-Based Representation of Gene Expression.Genes · 2022Article
- Challenges in ensuring the generalizability of image quantitation methods for MRI.Medical physics · 2022Review
Corrections and comments
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Authors and funding
5 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Machine learning algorithms are currently being implemented in an escalating manner to classify and/or predict the onset of some neurodegenerative diseases; including Alzheimer's Disease (AD); this could be attributed to the fact of the abundance of data and powerful computers. The objective of this work was to deliver a robust classification system for AD and Mild Cognitive Impairment (MCI) against healthy controls (HC) in a low-cost network in terms of shallow architecture and processing. In this study, the dataset included was downloaded from the Alzheimer's disease neuroimaging initiative (ADNI). The classification methodology implemented was the convolutional neural network (CNN), where the diffusion maps, and gray-matter (GM) volumes were the input images. The number of scans included was 185, 106, and 115 for HC, MCI and AD respectively. Ten-fold cross-validation scheme was adopted and the stacked mean diffusivity (MD) and GM volume produced an AUC of 0.94 and 0.84, an accuracy of 93.5% and 79.6%, a sensitivity of 92.5% and 62.7%, and a specificity of 93.9% and 89% for AD/HC and MCI/HC classification respectively. This work elucidates the impact of incorporating data from different imaging modalities; i.e. structural Magnetic Resonance Imaging (MRI) and Diffusion Tensor Imaging (DTI), where deep learning was employed for the aim of classification. To the best of our knowledge, this is the first study assessing the impact of having more than one scan per subject and propose the proper maneuver to confirm the robustness of the system. The results were competitive among the existing literature, which paves the way for improving medications that could slow down the progress of the AD or prevent it.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.