Neurology

An integrated machine learning and chemical space network approach for the design of potent epigenetic HDAC6 inhibitors for targeting neurological disorders.

Histone deacetylase 6 (HDAC6) is increasingly recognized as a key regulator of cytoskeletal dynamics and intracellular transport in both neurodevelopmental and neurodegenerative disorders. Despite the large number of HDAC6 inhibitors reported, only a few have shown effective in vivo activity in neurological disease models. In this context, machine-learning (ML) approaches offer a powerful strategy...

An interactive anatomy tool to boost clinical reasoning and knowledge retention for preclinical medical students: a preliminary evaluation.

INTRODUCTION: Anatomy teaching in preclinical medical education has become increasingly compressed, making it more difficult for students to integrate foundational anatomical knowledge with clinical reasoning. Upper limb nerve lesions are particularly challenging to learn because they require spatial understanding and application of structure-function relationships, yet students often struggle to ...

Cerebrospinal fluid volume outperforms traditional measures for predicting treatment failure in infant hydrocephalus.

BACKGROUND: Endoscopic third ventriculostomy with choroid plexus cauterization (ETV/CPC) offers an alternative to shunt placement for infant hydroceph...

Application Value of a nomogram integrating contrast-enhanced CT radiomics and clinical indicators in evaluating lymph node metastasis in pediatric peripheral neuroblastoma.

OBJECTIVE: To construct a machine learning model using contrast-enhanced CT radiomics and clinical indicators, aiming to improve the diagnostic accura...

The role of nitrogen dioxide in the prevalence of adverse cardiovascular and cerebrovascular diseases in China: a national multi-pollutant geospatial analysis.

INTRODUCTION: Cardiovascular and cerebrovascular diseases (CCVDs) pose a severe global health threat, particularly among middle-aged and elderly popul...

A Two-Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort.

OBJECTIVE: Isolated rapid-eye-movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due ...

Advancing stroke prevention in atrial fibrillation: a systematic review of machine learning-based risk prediction models.

BACKGROUND: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and confers a four to fivefold increase in ischemic stroke risk, ...

Recent Advances in Imaging of Demyelinating and Dysmyelinating White Matter Lesions.

White matter diseases encompass a heterogeneous spectrum of central nervous system disorders, with neuroimaging serving a pivotal role in their diagno...

An Explainable Machine Learning Model Integrating Transcranial Doppler and Clinical Data to Predict Outcomes After Endovascular Thrombectomy in Acute Ischemic Stroke.

BACKGROUND: Endovascular thrombectomy (EVT) has improved outcomes in patients with acute ischemic stroke due to large vessel occlusion (AIS-LVO); howe...

A Comprehensive Self-Medication Management System to Reduce Medication Errors Among People Living With Dementia: Mixed Methods Feasibility and Usability Study.

BACKGROUND: Medication adherence is a critical challenge for people living with dementia and their caregivers. Standard care relies on appropriate med...

Developments in the design and therapeutic applications of GSK3β inhibitors.

Glycogen synthase kinase-3β (GSK3β) has emerged as one of the most thoroughly validated therapeutic targets in modern drug discovery, with dysregulati...

Combined effects of cumulative triglyceride-glucose and blood pressure on stroke in middle-aged and older Chinese adults: a longitudinal analysis.

BACKGROUND: The triglyceride-glucose (TyG) index has increasingly been recognised an indicator for stroke risk. We aimed to explore the relationship b...

AI-driven multimodal retinal imaging for early detection and risk stratification of vascular and neurodegenerative diseases.

Systemic vascular and neurodegenerative disorders are important causes of disability and death worldwide, mainly because of the late stage of diagnosi...

Comparative evaluation of conventional radiomics and VGG-SAM fusion strategies for MRI-based preoperative prediction of perineural invasion in cervical cancer.

OBJECTIVE: Perineural invasion (PNI) is an adverse feature in cervical cancer and may influence nerve-sparing surgery. We compared conventional radiom...

Prediction and diagnosis of post-stroke epilepsy using artificial intelligence approaches: a systematic review and meta-analysis.

INTRODUCTION: Post-stroke epilepsy (PSE) is a common complication following a stroke and is a major cause of epilepsy in the elderly. Artificial intel...

A machine learning-derived speech index as a biomarker for Huntington's disease severity.

BACKGROUND: The development of disease-modifying therapies for Huntington's disease (HD) necessitates sensitive, scalable, and objective biomarkers fo...

Simultaneous partial volume correction and denoising of brain PET images, using transformers and transfer learning.

BACKGROUND: Positron emission tomography (PET) is a key tool for quantitative brain imaging, but its image quality and quantitative reliability are st...

A machine learning approach for early Parkinson's disease diagnosis based on brain texture features from T1-weighted imaging.

OBJECTIVE: To investigate the diagnostic value of subcortical texture features from T1-weighted MRI combined with machine learning for early Parkinson...

3D Registration-Guided Deformable Residual Inpainting for ssEM Restoration.

MOTIVATION: Serial section Electron Microscopy (ssEM) is essential for studying biological cell structures at nanometer resolution. However, Supportin...

Performance comparison between a deep learning model and spine surgeons in detecting cervical spinal cord compression on radiographs.

OBJECTIVE: This study aimed to develop a deep learning (DL) model for the detection of cervical spinal cord compression on cervical radiographs and co...