AI Medical Compendium Journal:
Frontiers in neurology

Showing 1 to 10 of 49 articles

Lean body mass and stroke volume, a sex issue.

Frontiers in neurology
INTRODUCTION: Large vessel occlusions (LVO) account for over 60% of stroke-related mortality and disability. Lean body mass (LBM) represents metabolically active body tissue and has been associated with reduced mortality. This study aimed to investig...

Development of a clinical-radiological nomogram for predicting severe postoperative peritumoral brain edema following intracranial meningioma resection.

Frontiers in neurology
OBJECTIVE: The goal of this study was to develop a nomogram that integrates clinical data to predict the likelihood of severe postoperative peritumoral brain edema (PTBE) following the surgical removal of intracranial meningioma.

The global research of magnetic resonance imaging in Alzheimer's disease: a bibliometric analysis from 2004 to 2023.

Frontiers in neurology
BACKGROUND: Alzheimer's disease (AD) is a common neurodegenerative disorder worldwide and the using of magnetic resonance imaging (MRI) in the management of AD is increasing. The present study aims to summarize MRI in AD researches via bibliometric a...

Development and validation of an explainable machine learning prediction model of hemorrhagic transformation after intravenous thrombolysis in stroke.

Frontiers in neurology
OBJECTIVE: To develop and validate an explainable machine learning (ML) model predicting the risk of hemorrhagic transformation (HT) after intravenous thrombolysis.

A deep learning model for carotid plaques detection based on CTA images: a two stepwise early-stage clinical validation study.

Frontiers in neurology
OBJECTIVE: To develop a deep learning (DL) model for carotid plaque detection based on CTA images and evaluate the clinical application feasibility and value of the model.

Prognostic value of multi-PLD ASL radiomics in acute ischemic stroke.

Frontiers in neurology
INTRODUCTION: Early prognosis prediction of acute ischemic stroke (AIS) can support clinicians in choosing personalized treatment plans. The aim of this study is to develop a machine learning (ML) model that uses multiple post-labeling delay times (m...

Predicting functional outcomes of patients with spontaneous intracerebral hemorrhage based on explainable machine learning models: a multicenter retrospective study.

Frontiers in neurology
BACKGROUND: Spontaneous intracerebral hemorrhage (SICH) is the second most common cause of cerebrovascular disease after ischemic stroke, with high mortality and disability rates, imposing a significant economic burden on families and society. This r...

Comparison of an AI-based mobile pupillometry system and NPi-200 for pupillary light reflex and correlation with glaucoma-related markers.

Frontiers in neurology
INTRODUCTION: Glaucoma is a leading cause of blindness, often progressing asymptomatically until significant vision loss occurs. Early detection is crucial for preventing irreversible damage. The pupillary light reflex (PLR) has proven useful in glau...

Changes in hematoma volume following aneurysmal subarachnoid hemorrhage and its impact on patient prognosis.

Frontiers in neurology
OBJECTIVE: This study aims to investigate the effects of preoperative intracerebral hematoma volume (HVpre), hematoma volume 6-8 days post-surgery (HVpost), and the rate of hematoma volume change (HVpre-HVpost)/HVpre on the prognosis of patients with...

Chlorfenapyr-related delayed rhabdomyolysis: a case series.

Frontiers in neurology
INTRODUCTION: Chlorfenapyr, a broad-spectrum insecticide and acaricide of the pyrrole-class pesticides, can induce dizziness, fatigue, profuse sweating, and altered consciousness by interfering with cell energy metabolism. However, chlorfenapyr-relat...