Neurology

Association of Deep Learning-based Chest CT-derived Respiratory Parameters with Disease Progression in Amyotrophic Lateral Sclerosis.

Background Forced vital capacity (FVC) is a standard measure of respiratory function in patients with amyotrophic lateral sclerosis (ALS) but has limitations, particularly for patients with bulbar impairment. Purpose To determine the value of deep learning-based chest CT-derived respiratory parameters in predicting ALS progression and survival. Materials and Methods This retrospective study includ...

Predicting Progression to Dementia Using Auditory Verbal Learning Test in Community-Dwelling Older Adults Based On Machine Learning.

BACKGROUND: Primary healthcare institutions find identifying individuals with dementia particularly challenging. This study aimed to develop machine learning models for identifying predictive features of older adults with normal cognition to develop dementia.

Machine Learning Assisted Stroke Prediction in Mechanical Circulatory Support: Predictive Role of Systemic Mitochondrial Dysfunction.

Stroke continues to be a major adverse event in advanced congestive heart failure (CHF) patients after continuous-flow left ventricular assist device ...

An Integrated Electroencephalography and Eye-Tracking Analysis Using eXtreme Gradient Boosting for Mental Workload Evaluation in Surgery.

ObjectiveWe aimed to develop advanced machine learning models using electroencephalogram (EEG) and eye-tracking data to predict the mental workload as...

Detection of Neurogenic Voice Disorders Using the Fisher Vector Representation of Cepstral Features.

Neurogenic voice disorders (NVDs) are caused by damage or malfunction of the central or peripheral nervous system that controls vocal fold movement. I...

Juvenile Myoclonic Epilepsy Imaging Endophenotypes and Relationship With Cognition and Resting-State EEG.

Structural neuroimaging studies of patients with Juvenile Myoclonic Epilepsy (JME) typically present two findings: 1-volume reduction of subcortical g...

A new network structure for Parkinson's handwriting image recognition.

Parkinson's disease (PD) remains a condition without a cure, though its early manifestations can be managed effectively by medical professionals. This...

Mapping minds not averages: a scalable subject-specific manifold learning framework for neuroimaging data

Mental and cognitive representations are believed to reside on low-dimensional, non-linear manifolds embedded within high-dimensional brain activity...

Rootlets-based registration to the spinal cord PAM50 template

Spinal cord functional MRI studies require precise localization of spinal levels for reliable voxelwise group analyses. Traditional template-based r...

xEEGNet: Towards Explainable AI in EEG Dementia Classification

This work presents xEEGNet, a novel, compact, and explainable neural network for EEG data analysis. It is fully interpretable and reduces overfittin...

Artificial Intelligence for Personalized Prediction of Alzheimer's Disease Progression: A Survey of Methods, Data Challenges, and Future Directions

Alzheimer's Disease (AD) is marked by significant inter-individual variability in its progression, complicating accurate prognosis and personalized ...

Towards Robust Multimodal Physiological Foundation Models: Handling Arbitrary Missing Modalities

Multimodal physiological signals, such as EEG, ECG, EOG, and EMG, are crucial for healthcare and brain-computer interfaces. While existing methods r...

HoloDx: Knowledge- and Data-Driven Multimodal Diagnosis of Alzheimer's Disease

Accurate diagnosis of Alzheimer's disease (AD) requires effectively integrating multimodal data and clinical expertise. However, existing methods of...

Neurophysiologically Realistic Environment for Comparing Adaptive Deep Brain Stimulation Algorithms in Parkinson Disease

Adaptive deep brain stimulation (aDBS) has emerged as a promising treatment for Parkinson disease (PD). In aDBS, a surgically placed electrode sends...

Enhancing Cochlear Implant Signal Coding with Scaled Dot-Product Attention

Cochlear implants (CIs) play a vital role in restoring hearing for individuals with severe to profound sensorineural hearing loss by directly stimul...

SPD Learning for Covariance-Based Neuroimaging Analysis: Perspectives, Methods, and Challenges

Neuroimaging provides a critical framework for characterizing brain activity by quantifying connectivity patterns and functional architecture across...

Nearly isotropic segmentation for medial temporal lobe subregions in multi-modality MRI

Morphometry of medial temporal lobe (MTL) subregions in brain MRI is sensitive biomarker to Alzheimers Disease and other related conditions. While T...

NRevisit: A Cognitive Behavioral Metric for Code Understandability Assessment

Measuring code understandability is both highly relevant and exceptionally challenging. This paper proposes a dynamic code understandability assessm...

Subject-independent Classification of Meditative State from the Resting State using EEG

While it is beneficial to objectively determine whether a subject is meditating, most research in the literature reports good results only in a subj...

A BERT-Style Self-Supervised Learning CNN for Disease Identification from Retinal Images

In the field of medical imaging, the advent of deep learning, especially the application of convolutional neural networks (CNNs) has revolutionized ...