Neurology

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 brain. For instance, current findings highlight the role of 2 specific misfolded proteins in Alzheimer which are believed to spread using brain fibers as highways. Previous studies investigated such spreading by simulation models or machine learning-based predictors which adopt the brain connectome...

Continuous Reaching and Grasping with a BCI Controlled Robotic Arm in Healthy and Stroke-Affected Individuals

Recent advancements in signal processing techniques have enabled non-invasive Brain-Computer Interfaces (BCIs) to control assistive devices, like robotic arms, directly with users’ EEG signals. However, the applications of these systems are currently limited by the low signal-to-noise ratio and spatial resolution of EEG from which brain intention is decoded. In this study, we propose a motor-image...

Artificial Intelligence for Short-Term Modified Rankin Score Prediction after Acute Stroke Symptoms Using Wrist-worn Triaxial Accelerometry Data

Functional outcomes after stroke are commonly assessed via modified Rankin Scale (mRS). However, mRS is subject to patient and assessor biases and is ...

Quantifying cortical lesions in large legacy multiple sclerosis clinical trial MRI datasets using multi-contrast post-processing and deep learning

Multiple sclerosis (MS) is a chronic neurological disease affecting both white and gray matter of the central nervous system. Despite the well-establi...

Statistical analysis for the development of a Deep Learning model for the classification of images with TDP-43 pathology

Diagnosing Amyotrophic Lateral Sclerosis (ALS) remains challenging due to its inherent heterogeneity. Cytoplasmic aggregation of TDP-43, observed in a...

A Novel Multi-Omics Deep Learning Framework for Spatiotemporal Cerebral Cortex Localization & Expression

Accurately mapping and predicting amino acid localization and gene expression patterns in the dorsolateral prefrontal cortex (DLPFC) is important for ...

Towards a diagnostic test for sporadic ALS utilising deep learning and SNP microarrays

A variety of common and rare genetic factors have been implicated in the development of amyotrophic lateral sclerosis (ALS), and the evidence is that ...

AutoRADP: An Interpretable Deep Learning Framework to Predict Rapid Progression for Alzheimer’s Disease and Related Dementias Using Electronic Health Records

Alzheimer’s disease (AD) and AD-related dementias (ADRD) exhibit heterogeneous progression rates, with rapid progression (RP) posing significant chall...

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 number of complex conditions, including cancer, hear...

Optic Nerve Lesion Volume, White Matter Hyperintensities, and Brain Volumetrics in Multiple Sclerosis: A Multi-Sequence MRI-Based Analysis

To investigate the relationship between optic nerve lesion volume (ONLV), measured on double inversion recovery (DIR) MRI, and other radiological biom...

Deep Learning Analysis of Figure Copying Tasks for Parkinson’s Disease Detection with GAN-Based Data Augmentation

Early and accurate diagnosis of Parkinson’s disease (PD) is essential for enabling timely treatment and effective disease management. In this study, w...

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 biological mechanisms, but the extent of their shared genet...

Diffusion-weighted Imaging And Retinal Oximetry Predict Functional Outcome After The First Episode Of Optic Neuritis

To evaluate diffusion weighted imaging (DWI) with advanced diffusion models, optical coherence tomography (OCT), and automatic retinal oximetry as pot...

Targeted Serum Metabolomic Profiling and Machine Learning Approach in Alzheimer’s Disease using the Alzheimer’s Disease Diagnostics Clinical Study (ADDIA) Cohort

Metabolic biomarkers can potentially be used for early diagnosis, prognostic risk stratification and/or early treatment and prevention of individuals ...

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 disequilibrium with APOE, has been associated with c...

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 disorder globally. Owing to its substantial herit...

Independent Evaluation of Deep Learning Models for Detecting Focal Cortical Dysplasia

The objective of this study is to perform an independent assessment of the diagnostic utility of three state-of-the-art tools for the detection of foc...

Brain Age Prediction in Type II GM1 Gangliosidosis

GM1 gangliosidosis is an inherited, progressive, and fatal neurodegenerative lysosomal storage disorder with no approved treatment. We calculated a pr...

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 timely clinical management and outcomes. Current dia...

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 overlapping clinical presentations. In this study, we ev...