Neurology

Dementia

Latest AI and machine learning research in dementia for healthcare professionals.

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DUNE: a versatile neuroimaging encoder captures brain complexity across three major diseases: cancer, dementia and schizophrenia

Magnetic resonance images (MRI) of the brain exhibit high dimensionality that pose significant chall...

Investigating the causal network of dementia by employing a causal discovery approach combined with natural language processing models

Comprehensively studying modifiable risk factors altogether to explore how they contribute to dement...

Leveraging functional annotations to map rare variants associated with Alzheimer’s disease with gruyere

The increasing availability of whole-genome sequencing (WGS) has begun to elucidate the contribution...

Integration of Deep Learning Annotations with Functional Genomics Improves Identification of Causal Alzheimer’s Disease Variants

Genetic variants associated with Alzheimer’s disease (AD) through genome-wide association studies (G...

Machine Learning Classification of Mild Cognitive Impairment using Advanced Multi-Shell Diffusion MRI and CSF Biomarkers

Machine learning applied to neuroimaging can help with medical diagnosis and early detection by iden...

Modeling the Spread of Misfolded Proteins in Alzheimer’s Disease using Higher-Order Simplicial Complex Contagion

Neurodegenerative diseases are characterized by complex proteins misfolded that propagate within the...

MRI2PET: Realistic PET Image Synthesis from MRI for Automated Inference of Brain Atrophy and Alzheimer’s

Positron Emission Tomography (PET) scans are a crucial tool in the diagnosing and monitoring of a nu...

Cross-Disorder Machine Learning Uncovers Schizophrenia Risk Variants Predictive of Alzheimer’s Disease

Alzheimer’s disease (AD) and Schizophrenia (SCZ) exhibit overlapping clinical features and biologica...

Genotyping TOMM40’523 Poly-T Polymorphisms Using Whole-Genome Sequencing

The TOMM40’523 poly-T repeat polymorphism (rs10524523), located in the TOMM40 gene and in linkage di...

Silencer variants are key drivers of gene upregulation in Alzheimer’s disease

Alzheimer’s disease (AD), particularly late-onset AD, stands as the most prevalent neurodegenerative...

Predicting Alzheimer’s Trajectory: A Multi-PRS Machine Learning Approach for Early Diagnosis and Progression Forecasting

Predicting the early onset of dementia due to Alzheimer’s Disease (AD) has major implications for ti...

Smartphone-based behavioral profiling for distinguishing Dementia with Lewy bodies from Alzheimer’s Disease

Dementia with Lewy bodies (DLB) is frequently misdiagnosed as Alzheimer’s disease (AD) due to overla...

A Task-Optimized Approach for High-Accuracy Alzheimer’s Diagnosis from Handwriting Data

Training complex models on Alzheimer’s Disease (AD) datasets is challenging due to the costly proces...

Leveraging Large Language Models for Identifying Interpretable Linguistic Markers and Enhancing Alzheimer’s Disease Diagnostics

Alzheimer’s Disease (AD) is a progressive irreversible neurodegenerative disorder. Early AD detectio...

DeepDrug2: A Germline-focused Graph Neural Network Framework for Alzheimer’s Drug Repurposing Validated by Electronic Health Records

Alzheimer’s disease (AD) is a complex neurodegenerative disorder with limited therapeutic options. T...

Neuroanatomical-Based Machine Learning Prediction of Alzheimer’s Disease Across Sex and Age

Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decl...

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