Neurology

DVAP-Reg: Dual-view anatomical prior-driven cross-dimensional registration for spinal surgery navigation.

2D-3D cross-dimensional registration serves as a critical technology in spinal surgery navigation, with profound implications for enhancing surgical precision, reducing radiation exposure and mitigating surgical risks. Its core objective is to achieve visual navigation by accurately aligning preoperative high-resolution 3D vertebrae with intraoperative 2D X-rays. However, this technology remains c...

Degraders on Demand: Engineering Smart Nanocarriers for PROTAC Delivery.

Proteolysis-targeting chimeras (PROTACs) are transforming targeted therapeutics by enabling the selective and catalytic degradation of disease-associated proteins, offering new treatment avenues in oncology, neurodegeneration, immunology, and infectious diseases. However, their clinical translation is limited by poor membrane permeability, low oral bioavailability, suboptimal pharmacokinetics, a n...

Machine Learning-Enhanced Hyperspectral Raman Imaging for Label-Free Molecular Atlas of Alzheimer's Brain.

Label-free molecular imaging that enables the construction of a molecular atlas of biological tissues is vital for understanding complex physiological...

Deep learning-based cognitive impairment brain imaging analysis: New methods, new technologies, and new paradigms.

Cognitive impairment arising from ischemic stroke, Alzheimer's disease, and Parkinson's disease presents distinct structural and network-level alterat...

Early Alzheimer's disease classification via structure and feature-based graph attention network from multi-center data.

With the increasing Alzheimer's disease (AD) prevalence, morbidity, and mortality, its early diagnosis is particularly important. The multi-modal data...

Speech Biomarkers From Smartphone Calls Track Progression in REM Sleep Behavior Disorder and Parkinson's Disease.

OBJECTIVE: This 24-month longitudinal study involving isolated rapid eye movement sleep behavior disorder (iRBD), early-stage Parkinson's disease (PD)...

Smiling difficulties in Alzheimer's disease linked to reduced nucleus accumbens and pallidum brain volume: Deep learning insights.

Patients tend to lose the ability to smile during the course of dementia. However, such impairments have rarely been reported, likely due to challenge...

Spinal circuit mechanisms constrain therapeutic windows for ALS intervention: A computational modeling study.

Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease characterized by progressive breakdown of neural circuits which leads to moto...

Stress detection using the phase controlled Bi-channel adaptive features from the brain EEG signals.

This work proposes a stress classification system from the electroencephalogram (EEG) signals collected from the stress subjects. The scheme extracts ...

Functional neuroimaging features for predicting the transition from benign paroxysmal positional vertigo to persistent postural-perceptual dizziness.

ObjectivesBenign paroxysmal positional vertigo (BPPV) is a prevalent triggers of persistent postural-perceptual dizziness (PPPD). The maladaptation of...

Modelling seizure-related predictors of epilepsy diagnostic gap in two urban informal settlements of Nairobi using machine learning.

BACKGROUND: There is a wide gap in epilepsy diagnosis, particularly in low- and middle-income countries. We used machine learning models to identify s...

Efficacy and safety of recombinant human bone morphogenetic protein-2 biomaterials in promoting bone regeneration: A systematic review and meta-analysis.

OBJECTIVES: This study aims to systematically evaluate the efficacy and safety of recombinant human bone morphogenetic protein-2 (rhBMP-2) in promotin...

Biotypes of deeply phenotyped depressed patients reflect signatures of adverse childhood experience and depressive cognitive biases.

BACKGROUND: Negative Cognitive Styles (NCS) are key features of depression contributing to severe clinical outcomes by sustaining negative affect. How...

NAD+ restores proteostasis through splicing-dependent autophagy.

Autophagy preserves neuronal integrity by clearing damaged proteins and organelles, but its efficiency declines with aging and neurodegeneration. Depl...

Spatial radiomics-based interpretable multimodal machine learning model enhances outcomes prediction for minor stroke: A multicenter cohort study.

INTRODUCTION: Accurately identifying unfavorable outcomes is crucial for the clinical management of minor stroke. Conventional imaging prediction mode...

Machine learning in stroke and its sequelae: a narrative review of clinical applications and emerging trends.

OBJECTIVE: This narrative review synthesizes machine learning (ML) applications across the stroke and post-stroke continuum from acute imaging and dia...

Fully automated quantification of net water uptake in acute ischemic stroke using only non-contrast CT imaging.

OBJECTIVE: Estimating early lesion progression in ischemic stroke is essential for assessing thrombolytic treatment efficacy. While computed tomograph...

Automating wound assessment: convolutional neural network-based mobile application for SINBAD classification system.

INTRODUCTION: Diabetic foot ulcer (DFU) assessment using the SINBAD system is essential for clinical decision-making but often limited by access to sp...

Deep Learning-Based Brainstem Segmentation and Multi-Class Classification for Parkinsonian Syndrome.

BACKGROUND: Brain segmentation using structural MRI is effective for identifying regional atrophy in Parkinsonian syndromes. However, clinical validat...

The Application Effect of Robot-Assisted Therapy for Hand Dysfunction After Stroke: A Scoping Literature Review.

This scoping review was designed to address the core question: In the field of poststroke hand function rehabilitation, what is the current status of ...