AIMC Topic: Ischemic Stroke

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Workflow improvements from automated large vessel occlusion detection algorithms are dependent on care team engagement.

Journal of neurointerventional surgery
BACKGROUND: Automated machine learning (ML)-based large vessel occlusion (LVO) detection algorithms have been shown to improve in-hospital workflow metrics including door-to-groin time (DTG). The degree to which care team engagement and interaction a...

Collaborative artificial intelligence for the diagnosis and management of acute ischemic stroke.

Annals of medicine
BACKGROUND: Acute Ischemic Stroke (AIS) remains a critical global health challenge that requires continuous improvement in diagnostic strategies. Timely and accurate diagnosis is essential for effective reperfusion therapies such as intravenous throm...

Identification of coagulation-related hub genes in ischemic stroke based on bioinformatics integration analysis and investigation of their immune regulatory mechanisms.

European journal of medical research
BACKGROUND: Ischemic stroke (IS) is a cerebrovascular disease resulting from insufficient blood supply to specific areas of the brain, often due to atherosclerosis and thrombosis. While the association between polymorphisms in coagulation-related gen...

Deep-learning-based non-contrast CT for detecting acute ischemic stroke: a systematic review and HSROC meta-analysis of patient-level diagnostic accuracy.

BMC neurology
BACKGROUND: Non-contrast CT (NCCT) is first-line imaging for suspected acute ischemic stroke (AIS) but has limited early sensitivity; deep learning (DL) may improve patient-level detection.

Development and Validation of a Web-Based Machine Learning Model for Predicting Early Neurological Deterioration Following Stroke Thrombolysis: Multicenter Study.

Journal of medical Internet research
BACKGROUND: Early neurological deterioration (END) significantly worsens outcomes in patients with acute ischemic stroke (AIS) receiving intravenous thrombolysis, yet clinicians lack reliable tools to identify high-risk patients who need intensified ...

Unsupervised discovery of ischemic stroke phenotypes from multimodal MRI radiomics.

Biomedical physics & engineering express
This study presents a fully unsupervised and label-independent radiomic pipeline designed to group different types of ischemic stroke lesions using multimodal Magnetic Resonance Imaging (MRI) . The aim is to address lesion heterogeneity and the absen...

Both Infarcted and Noninfarcted Brain Regions Contribute to Deep Learning-Based MRI Prediction of Acute Stroke Outcome.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Predicting long-term clinical outcomes based on early acute ischemic stroke (AIS) information would be useful for many reasons, including patient counseling and clinical trial execution. This study investigates how different r...

Artificial Intelligence-Driven Detection of Large Vessel Occlusions on NCCT: A Multi-Institutional Study.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Imaging triage of stroke patients is primarily based on perfusion imaging. Simplified triage based on non-contrast CT are limited (NCCT). To evaluate the predictive capability of a deep learning algorithm, "Triage Stroke" (Bra...

Temporal shifts in prognostic factors for 90- and 180-day outcomes after stroke thrombolysis: A machine learning analysis.

PloS one
INTRODUCTION: Prognostication at 90 and 180 days after thrombolysis for acute ischemic stroke (AIS) is critical, yet the temporal evolution of key predictors remains inadequately understood. The utility of machine learning for systematically comparin...

Joint impact of stress hyperglycaemic ratio and glycaemic variability in patients with ischaemic stroke and machine learning for mortality prediction.

BMC neurology
BACKGROUND: The global burden of ischaemic stroke (IS) is high, which is potentially relevant to stress hyperglycemia ratio (SHR) and glycaemic variability (GV). This study aims to evaluate the combined effect of the SHR and GV with predict short-ter...