Neurology

Role of Artificial Intelligence in Musculoskeletal Interventions.

Artificial intelligence (AI) has rapidly emerged as a transformative force in musculoskeletal imaging and interventional radiology. This article explores how AI-based methods-including machine learning (ML) and deep learning (DL)-streamline diagnostic processes, guide interventions, and improve patient outcomes. Key applications discussed include ultrasound-guided procedures for joints, nerves, an...

Long-Term Neonatal EEG Modeling with DSP and ML for Grading Hypoxic-Ischemic Encephalopathy Injury.

Hypoxic-Ischemic Encephalopathy (HIE) occurs in patients who experience a decreased flow of blood and oxygen to the brain, with the optimal window for effective treatment being within the first six hours of life. This puts a significant demand on medical professionals to accurately and effectively grade the severity of the HIE present, which is a time-consuming and challenging task. This paper pro...

Exploring oculomotor challenges in amyotrophic lateral sclerosis: a comprehensive review.

Traditionally understood as a motor neuron disease, amyotrophic lateral sclerosis (ALS) is now recognized to involve broader neurodegenerative process...

Deep Learning for EEG-Based Visual Classification and Reconstruction: Panorama, Trends, Challenges and Opportunities.

Deep learning has significantly enhanced the research on the emerging issue of Electroencephalogram (EEG)-based visual classification and reconstructi...

Deep learning for Parkinson's disease classification using multimodal and multi-sequences PET/MR images.

BACKGROUND: We aimed to use deep learning (DL) techniques to accurately differentiate Parkinson's disease (PD) from multiple system atrophy (MSA), whi...

Enhanced Graph Attention Network by Integrating Transformer for Epileptic EEG Identification.

Electroencephalography signal classification is essential for the diagnosis and monitoring of neurological disorders, with significant implications fo...

Circulating Antioxidant Nutrients and Brain Age in Midlife Adults.

OBJECTIVE: Due to population aging, the increasing prevalence of Alzheimer's Disease (AD) and related dementias are major public health concerns. Diet...

AI-Driven Advances in Parkinson's Disease Neurosurgery: Enhancing Patient Selection, Trial Efficiency, and Therapeutic Outcomes.

Parkinson's disease (PD) is a progressive neurodegenerative disorder marked by motor and non-motor dysfunctions that severely compromise patients' qua...

Mortality and its predictors among people with dementia receiving psychiatric in-patient care.

BACKGROUND: Although dementia is a terminal condition, palliation can be a challenge for clinical services. As dementia progresses, people frequently ...

Identifying Common Disease Trajectories of Progressive Supranuclear Palsy with Electronic Health Records.

BACKGROUND: Progressive supranuclear palsy (PSP) is a rare neurodegenerative disorder characterized by parkinsonism and impairments in balance, langua...

Assessing and validating machine learning-enhanced imputation of admission American Spinal Injury Association Impairment Scale grades for spinal cord injury.

OBJECTIVE: The American Spinal Injury Association Impairment Scale (AIS) assigned at patient admission is an important predictor of outcomes following...

Machine learning-based prediction of 90-day prognosis and in-hospital mortality in hemorrhagic stroke patients.

This study aims to predict hemorrhagic stroke outcomes, including 90-day prognosis and in-hospital mortality, using machine learning models and SHaple...

Usability testing a web application to support evidence-based commissioning decisions for implementing mobile stroke units.

Commissioning of innovations in healthcare is a complex socio-technical process, ideally informed by high quality evidence. However, evidence is not a...

Novel neural activity profiles underlying inhibitory control deficits of clinical relevance in ADHD - insights from EEG tensor decomposition.

BACKGROUND: Attention-Deficit-Hyperactivity Disorder (ADHD) is a multifaceted neurodevelopmental disorder that impacts cognitive control processes. Wh...

Artificial Intelligence in Vascular Neurology: Applications, Challenges, and a Review of AI Tools for Stroke Imaging, Clinical Decision Making, and Outcome Prediction Models.

PURPOSE OF REVIEW: Artificial intelligence (AI) promises to compress stroke treatment timelines, yet its clinical return on investment remains uncerta...

Wearable sleep recording augmented by artificial intelligence for Alzheimer's disease screening.

The recent emergence of wearable devices will enable large scale remote brain monitoring. This study investigated whether multimodal wearable sleep re...

ADNP-15: An Open-Source Histopathological Dataset for Neuritic Plaque Segmentation in Human Brain Whole Slide Images with Frequency Domain Image Enhancement for Stain Normalization

Alzheimer's Disease (AD) is a neurodegenerative disorder characterized by amyloid-beta plaques and tau neurofibrillary tangles, which serve as key h...

GlyphMastero: A Glyph Encoder for High-Fidelity Scene Text Editing

Scene text editing, a subfield of image editing, requires modifying texts in images while preserving style consistency and visual coherence with the...

Evaluating the Effectiveness of Geant4 Software in Measuring the Damage Caused by Ti48 Ion Radiation on Nerve Cells, in Comparison to the Biophysical Model and Empirical Data.

INTRODUCTION: Presently, heavy particle ion radiation therapy is commonly utilized for the treatment of deep-seated malignancies, such as brain tumors...

Identifying Molecular Properties of Ataxin-2 Inhibitors for Spinocerebellar Ataxia Type 2 Utilizing High-Throughput Screening and Machine Learning.

Spinocerebellar ataxia type 2 (SCA2) is an autosomal dominant neurodegenerative disorder marked by cerebellar dysfunction, ataxic gait, and progressiv...