Deep learning applications in vascular dementia using neuroimaging

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Prediction of White Matter Hyperintensity in Brain MRI Using Fundus Photographs via Deep Learning

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Fully Automatic Classification of Brain Atrophy on NCCT Images in Cerebral Small Vessel Disease: A Pilot Study Using Deep Learning Models

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Using transfer learning for automated microbleed segmentation

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Artificial intelligence-driven intelligent learning models for identification and prediction of cardioneurological disorders: A comprehensive study

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Early Diagnosis of Alzheimer’s Disease Using Machine Learning in MCI Individuals

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Explainable AI-Driven Diagnostic Framework for Early Vascular Dementia Detection Using MRI

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Artificial Intelligence Assisted Vascular Dementia Disease Identification Using Optimized Neural Classification Procedure

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HVN-CLS: A Hierarchical Vascular Neural Classification System for Accurate Vascular Dementia Diagnosis using Adaptive Learning Strategy

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VD-DeepFusionNet: A Multi-Modal Hybrid Deep Learning Framework for Early Vascular Dementia Detection using Optimized Feature Integration

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Classification of Subcortical Vascular Cognitive Impairment Using Single MRI Sequence and Deep Learning Convolutional Neural Networks

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Classification of Vascular Dementia on magnetic resonance imaging using deep learning architectures

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Optimizing Vascular Dementia:A Deep Learning Framework Using CNN and RNN on MRI Data

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VascuDetect-Fusion: A Hybrid Autoencoder–Support Vector Machine Model for Accurate Vascular Dementia Diagnosis

Nadhiya, S., & Ramkumar, G. (2025) · International Conference on Recent Innovation in Science Engineering and Technology (ICRISET) · doi:10.1109/icriset64803.2025.11252429 · Cited by 1 · see citing works

NeuroVascX: A Hybrid Transformer–Extreme Gradient Boosting Framework for Vascular Dementia Identification

Nadhiya, S., & Ramkumar, G. (2025) · International Conference on Recent Innovation in Science Engineering and Technology (ICRISET) · doi:10.1109/icriset64803.2025.11252292