Neurology

Current Concepts on Imaging and Artificial Intelligence of Osteosarcopenia in the Aging Spine - A Review for Spinal Surgeons by the SRS Adult Spinal Deformity Task Force on Senescence.

STUDY DESIGN: Narrative review.

Unveiling the role of local metabolic constraints on the structure and activity of spiking neural networks.

Understanding the intricate interplay between neural dynamics and metabolic constraints is crucial for unraveling the mysteries of the brain. Despite the significance of this relationship, specific details concerning the impact of metabolism on neuronal dynamics and neural network architecture remain elusive, creating a notable gap in the existing literature. This study employs an energy-dependent...

FedOcw: optimized federated learning for cross-lingual speech-based Parkinson's disease detection.

Accurate detection of Parkinson's disease (PD) through speech analysis holds great promise for early diagnosis and improved patient management. Howeve...

Prediction of NIHSS Scores and Acute Ischemic Stroke Severity Using a Cross-attention Vision Transformer Model with Multimodal MRI.

RATIONALE AND OBJECTIVES: This study aimed to develop and evaluate models for classifying the severity of neurological impairment in acute ischemic st...

Visualizing nuclear pore complex plasticity with pan-expansion microscopy.

The exploration of cell-type and environmentally responsive nuclear pore complex (NPC) plasticity requires new, accessible tools. Using pan-expansion ...

Fusion of FDG and FMZ PET Reduces False-Positives in Predicting Epileptogenic Zone.

BACKGROUND AND PURPOSE: Epilepsy, a globally prevalent neurologic disorder, necessitates precise identification of the epileptogenic zone (EZ) for eff...

Clinical correlates of data-driven subtypes of deep gray matter atrophy and dopamine availability in early Parkinson's disease.

Recent machine-learning techniques may be useful to identify subtypes with distinct spatial patterns of biomarker abnormality in the various neurodege...

Regional and whole-brain neurofunctional alterations during pain empathic processing of physical but not affective pain in migraine patients.

BACKGROUND: Accumulating evidence suggests that migraine patients present abnormal brain responses to salient sensory and emotional stimuli. However, ...

DBSCAN and DBCV application to open medical records heterogeneous data for identifying clinically significant clusters of patients with neuroblastoma.

Neuroblastoma is a common pediatric cancer that affects thousands of infants worldwide, especially children under five years of age. Although recovery...

Optimizing Dementia Diagnosis Through Distance-Correlation Feature Space and Dimensionality Reduction.

The reduction of dimensionality in machine learning and artificial intelligence problems constitutes a pivotal element in the simplification of models...

Precision-Optimised Post-Stroke Prognoses.

BACKGROUND: Current medicine cannot confidently predict who will recover from post-stroke impairments. Researchers have sought to bridge this gap by t...

Patterns of calcitonin gene-related peptide monoclonal antibody use in people with migraine: Results of the OVERCOME (US) study.

BackgroundUnderstanding characteristics and reasons associated with using calcitonin gene-related peptide monoclonal antibodies (CGRP mAb) for migrain...

Providing context: Extracting non-linear and dynamic temporal motifs from brain activity.

Approaches studying the dynamics of resting-state functional magnetic resonance imaging (rs-fMRI) activity often focus on time-resolved functional con...

Predicting Stroke-Associated Pneumonia in Acute Ischemic Stroke: A Machine Learning Model Development and Validation Study with CBC-Derived Inflammatory Indices.

PURPOSE: Stroke-associated pneumonia (SAP), a critical complication of ischemic stroke, significantly worsens outcomes. Our aim was to identify SAP ri...

Multivariate and Machine Learning-Derived Virtual Staining and Biochemical Quantification of Cancer Cells through Raman Hyperspectral Imaging.

Advances in virtual staining and spatial omics have revolutionized our ability to explore cellular architecture and molecular composition with unprece...

Massively parallel genetic perturbation suggests the energetic structure of an amyloid-β transition state.

Amyloid aggregates are pathological hallmarks of many human diseases, but how soluble proteins nucleate to form amyloids is poorly understood. Here, w...

POC-CSP: a novel parameterised and orthogonally-constrained neural network layer for learning common spatial patterns (CSP) in EEG signals.

. Common spatial patterns (CSPs) has been established as a powerful feature extraction method in EEG signal processing with machine learning, but it h...

Current applications and outcomes of AI-driven adaptive learning systems in physical rehabilitation science education: A scoping review protocol.

Rationale Integrating artificial intelligence (AI) into education has introduced transformative possibilities, particularly through adaptive learning ...

An ensemble-based 3D residual network for the classification of Alzheimer's disease.

Alzheimer's disease (AD) is a common type of dementia, with mild cognitive impairment (MCI) being a key precursor. Early MCI diagnosis is crucial for ...

Automated classification of seizure onset pattern using intracranial electroencephalogram signal of non-human primates.

To develop and validate a machine learning framework for the classification of distinct seizure onset patterns using intracranial EEG (iEEG) recording...