Neurology

Noninvasive neurophysiological diagnostics of delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage: a scoping review.

BACKGROUND: Delayed cerebral ischemia (DCI) is a major complication following aneurysmal subarachnoid hemorrhage (aSAH), affecting outcomes. Given its multifactorial pathophysiology, including vasospasm, microcirculatory dysfunction, and neuroelectric disturbances, a range of diagnostic modalities has been studied. Neurophysiological techniques such as transcranial Doppler (TCD), electroencephalog...

A novel intelligent hybrid reinforcement learning framework for autonomous decision making in complex health cognitive systems.

Existing reinforcement learning (RL) approaches struggle to balance real-time decision-making with adaptive learning in dynamic healthcare environments. We propose a brain-inspired hybrid RL framework that integrates model-based (MB) planning and model-free (MF) reflexes via a dynamic meta-controller, neuro-symbolic clinical knowledge, counterfactual reasoning, and ethical safeguards. The framewor...

Insights into SIRT2 inhibition from machine learning-assisted multi-level screening of the NCI database.

The nicotinamide adenine dinucleotide (NAD+)-dependent deacetylase Sirtuin 2 (SIRT2) plays a regulatory function in diverse cellular processes and has...

A deep hybrid CNN-BiLSTM-BiGRU architecture with explainability for mild cognitive impairment detection using EEG.

Accurate detection of Mild Cognitive Impairment (MCI) is critical for timely intervention and for slowing progression to Alzheimer's disease. Electroe...

A multi-view TSK fuzzy system with deformable Gaussian membership functions and rule-level attention for classification.

This study presents a novel multi-view TSK fuzzy system that integrates deformable Gaussian membership functions with a rule-level attention mechanism...

Determinants and Machine Learning Prediction of Subtherapeutic Sodium Valproate Concentrations in Epilepsy Management in Xinjiang, China.

BACKGROUND AND OBJECTIVE: Valproic acid is a classic antiepileptic drug; however, it is characterized by a narrow therapeutic window, limited safety m...

Multi-dimensional MRI representation and privileged learning approaches to functional outcome prediction for ischemic stroke patients.

Accurate prediction of long-term functional outcomes for stroke patients remains a clinical challenge, despite advances in diagnostics and treatments....

Implementation of artificial intelligence to automate physical disector in a fractionator design for quantification of stem cell-derived neurons.

Accurate quantification of stem cell-derived dopaminergic neurons is essential for advancing cell therapy strategies in Parkinson's disease (PD). Trad...

Early diagnosis of Alzheimer's disease through handwriting analysis and deep learning: A review.

Alzheimer's disease (AD) is one of the most prevalent neurodegenerative disorders worldwide, requiring early identification for timely intervention an...

Prenatal serotonin reuptake inhibitor exposure and maternal depression symptoms are associated with altered fetal brain and placental development.

Maternal mental health is associated with fetal neurodevelopment. Identifying effective treatments for maternal psychiatric conditions is a public hea...

Parkinson's disease severity is encoded by non-linear oscillatory interactions across cortical-subcortical networks.

Parkinson's Disease (PD) is characterized by motor symptoms linked to dysregulated neural activity within basal ganglia-thalamocortical (BGTC) circuit...

The association between plasma IgG N-glycosylation and viral encephalitis in children: a hospital-based case-control study.

BACKGROUND: Viral encephalitis (VE) is an acute inflammatory disease caused by viral infection. Children are at a significantly higher risk of develop...

Superlearner can predict in-hospital mortality risk in critically ill patients with ischemic stroke: development and international validation.

BACKGROUND: Critically ill patients with ischemic stroke face substantial in-hospital mortality. Early and accurate prediction of mortality risk may f...

Intracranial compliance monitoring using pulse shape index in traumatic brain injury: relation to cerebral physiology and clinical outcome.

BACKGROUND: The intracranial pressure (ICP) pulse waveform reflects intracranial compliance. The pulse shape index (PSI), an artificial intelligence (...

An LC-MS-guided AI enabled serum molecule-interpretable SERS platform for exploratory metabolomic analysis in Alzheimer's disease.

Label-free surface-enhanced Raman spectroscopy (SERS) offers a promising avenue for rapid metabolic phenotyping in complex biofluids, yet its translat...

Brain-age defines a structural signature of outcomes after vagus nerve stimulation in children.

INTRODUCTION: Outcomes following vagus nerve stimulation (VNS) are difficult to predict prior to surgery in pediatric drug-resistant epilepsy (DRE). W...

Development of AI-assisted 3D-printed degradable hydrogel microneedles for transdermal delivery of progesterone-loaded solid lipid nanoparticles: a novel approach to slowing Alzheimer's disease progression.

Progesterone (PG) is used to slow the progression of neurodegenerative diseases, particularly Alzheimer's disease (AD) in postmenopausal women. Howeve...

Longitudinal Degeneration of Microstructural and Structural Connectivity Patterns Following Stroke.

BACKGROUND: Stroke causes neurological impairment through local plasticity mechanisms, such as synaptic sprouting, and large-scale network reorganizat...

AI-Driven Mapping of Seizure Spread Patterns.

OBJECTIVE: The focus of epilepsy research has largely been on seizure onset; however, physicians typically examine the patterns of seizure spread past...

Artificial intelligence in the assessment of epilepsy-related genetic mutations: Learned from GABAA receptors and GABA transporter 1.

This review examines how recent genetic and technological advances have transformed our understanding and treatment of genetic epilepsies (GEs), with ...