Neurology

Is chronic low back pain related to sleep disturbances? A self-organizing maps for unsupervised machine learning-based patient phenotyping.

BACKGROUND CONTEXT: Chronic low back pain (CLBP) is a multifactorial condition and a leading cause of disability worldwide. Among the various contributors to symptom persistence, sleep quality has emerged as a critical yet underexplored factor. Evidence suggests a bidirectional relationship between poor sleep and pain intensity, disability, and psychological distress in individuals with CLBP. PURP...

Evaluation of AI-based nerve segmentation on ultrasound. Response to Br J Anaesth 2025; 135: 1847-8.

Rapid Free-Breathing and Automated 2D Shimming of the Lung at 3T.

PURPOSE: To develop and validate a rapid, fully automated method for shimming of the lung. METHODS: For field mapping of the lung, a custom 2D RF spoi...

Leveraging hemispheric asymmetry in structural MRI with an attention-guided 3D CNN for early prediction of Alzheimer's conversion.

Early identification of mild cognitive impairment (MCI) progressing to Alzheimer's disease (AD) is of paramount importance. Despite the notable advanc...

Synergistic mitochondrial homeostasis regulation and cholinergic circuits reconstruction via a one-step synthesized multifunctional hydrogel facilitates spinal cord injury repair.

Neural Stem Cells (NSCs) possess significant potential to form new neural networks. However, following spinal cord injury (SCI), mitochondrial dysfunc...

Machine learning for automated differentiation of parkinson's disease and its mimics using ¹²³I-mIBG scintigraphy: insights from a multicentre real-world cohort (ITA-mIBG study).

PURPOSE: To assess machine learning (ML) classifiers trained on harmonised multicentre ¹²³I-mIBG planar scintigraphy for differentiating Parkinson's d...

Synergistic integration of clinical and multi-omics data for early MCI diagnosis using an attention-based graph fusion network.

BACKGROUND: Mild cognitive impairment (MCI), a precursor to Alzheimer's disease (AD), requires precise early diagnosis. Single-omics approaches often ...

The role of artificial intelligence in estimating stroke events in Moyamoya patients: A systematic review and meta-analysis of diagnostic test accuracy.

INTRODUCTION: Moyamoya disease (MMD) and syndrome (MMS) are rare cerebrovascular arteriopathies marked by progressive internal carotid stenosis, fragi...

Multi-omics integration identifies CACNG3 as a synaptic calcium channel regulator in Alzheimer's disease: Mechanistic insights and therapeutic implications.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, memory impairment, and impaired daily functio...

Artificial intelligence in psychiatry: Current and emerging trends, clinical applications, and research gaps explored through a bibliometric analysis.

OBJECTIVE: The aim of this study is to analyze AI-based scientific publications in psychiatry using bibliometric methods to identify prominent themes,...

Altered resting-state sensorimotor network in patients with obsessive-compulsive disorder: An EEG study.

BACKGROUND AND OBJECTIVE: Dysfunction in the cortical-striatal-thalamo-cortical circuit is considered a core pathological mechanism of obsessive-compu...

An Artificial Intelligence-Based Prognostic Model for Prediction of Functional Glaucoma Progression From Clinical and Structural Data.

PURPOSE: Integration of various sources of information for prediction of disease progression is an unmet need in glaucoma diagnostics. We designed a d...

Identification of phosphodiesterase 10 A modulators for neurodegenerative and psychiatric disorders: Combination of physics-based virtual screening and machine learning approaches.

Phosphodiesterase (PDE) is a crucial enzyme that regulates intracellular signal transduction by breaking down cyclic adenosine monophosphate (cAMP) an...

Enlarged cavum septum pellucidum & increased incidence of schizophrenia: Narrative review for neurodevelopmental correlate.

Schizophrenia being a major psychiatric disorder comprises of dominant neurodevelopmental corroborations; still there are inadequate markers which rev...

Long non-coding RNAs in human peripheral blood as biomarkers for age prediction.

Chronological age is a critical biological trait with substantial relevance in forensic investigations. Growing evidence highlights the role of long n...

Longitudinal changes in subcortical functional connectivity during Alzheimer's disease progression.

Human cognition and behavior rely on the integration of large-scale neural networks that connect the cerebral cortex and subcortical structures. Emerg...

Predicting Postoperative Discharge Status and Readmissions in Spinal Metastatic Disease Using Machine Learning Models.

Operative management of spinal metastatic disease is largely for symptom palliation rather than curative and revolves around the expectation that post...

Identifying diagnostic neuroimaging biomarkers for adolescent major depressive disorder.

BACKGROUND: The increasing incidence of adolescent depression represents a serious public health concern. Despite clear diagnostic criteria, the wide ...

Multi-Domain Dynamic Weighting Network for Motor Imagery Decoding.

In motor imagery (MI)-based brain-computer interfaces (BCIs), convolutional neural networks (CNNs) are widely employed to decode electroencephalogram ...

Cerebral hemodynamics and functional connectivity in the stroop test in Parkinson's disease patients: A machine learning approach to fNIRS features.

BACKGROUND: Cognitive impairment is a core non-motor feature of Parkinson's disease (PD). This study aimed to: (1) assess PD patients' performance on ...