Home › Research › Topics › convolutional
convolutional
205 studies tagged convolutional, dated 2006-12-06 to 2026-10-30. Bibliography: BibTeX (.bib) · RIS (.ris)
Newest in this topic
- Tau-CTFP: A connectome-informed continuous-time first-passage model for forecasting the onset of regional tau PET abnormality 2026-10-30
- A Wasserstein Weisfeiler-Lehman Kernel Framework for Multimodal Brain Connectome Analysis 2026-10-29
- Current gaps in downstream applications of fMRI foundation models: lessons learned from BrainLM & BrainHarmonix on Prevent-AD 2026-10-26
Studies
205 studies carry this tag.
Date range
2006 to 2026
Top journals
- Research Square 22
- medRxiv 22
- NeuroImage 14
- bioRxiv 14
- Preprints.org 7
87 journals in all.
Newest first, then by address. Each study has a usefulness score out of 100 (rubric version 4.0); tap a score to see what makes it up. Tags were assigned automatically from each study's title and summary. The same studies as a filter in the library.
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Machine learning methods pool diverse information to perform computer-assisted diagnosis and predict future clinical decline.
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The early identification of brain anatomy deviating from the normal pattern of growth and atrophy, such as in Alzheimer's disease (AD), has the potential to improve clinical outcomes through early intervention.
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Structural and functional brain images are playing an important role in helping us understand the changes associated with neurological disorders such as Alzheimer's disease (AD).
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We present iCluster, a fast and efficient algorithm that clusters a set of images while co-registering them using a parameterized, nonlinear transformation model.
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The early detection of subjects with probable Alzheimer's disease (AD) is crucial for effective appliance of treatment strategies.
From across this tag
9 of the 205 studies in this tag, picked by a fixed rule (a hash of each study's address), not by score or date; each page of this list shows a different 9. The same 9 appear here every time.
- Assessment of the predictive potential of cognitive scores from retinal images and retinal fundus metadata via deep learning using the CLSA database
- Predicting conversion from MCI to AD using resting-state fMRI, graph theoretical approach and SVM
- Deep learning detection of informative features in tau PET for Alzheimer’s disease classification
- Artificial intelligence framework identifies candidate targets for drug repurposing in Alzheimer's disease
- AI on Alzheimer Disease: Large-Scale Reproduction Shows the Field’s Hypotheses Cannot Be Distinguished on Common Data
- A drug repositioning algorithm based on a deep autoencoder and adaptive fusion
- Generalizing Amyloid β Pathology from Postmortem Human Brains with Vision Foundation Models for Lesion Quantification
- Early detection of dementia through retinal imaging and trustworthy AI
- Hippocampal surface analysis using discrete Ricci flow and Riemannian metrics for the diagnosis of Alzheimer's disease