AIMC Topic: Stroke

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Can CTA-Based Machine Learning Identify Patients for Whom Successful Endovascular Stroke Therapy Is Insufficient?

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Despite advances in endovascular stroke therapy (EST) devices and techniques, many patients are left with substantial disability, even if the final infarct volumes (FIVs) remain small. Here, we evaluate the performance of a ma...

Automated Emergent Large Vessel Occlusion Detection Using Viz.ai Software and Its Impact on Stroke Workflow Metrics and Patient Outcomes in Stroke Centers: A Systematic Review and Meta-analysis.

Translational stroke research
The implementation of artificial intelligence (AI), particularly Viz.ai software in stroke care, has emerged as a promising tool to enhance the detection of large vessel occlusion (LVO) and to improve stroke workflow metrics and patient outcomes. The...

Association and prediction of serum lipid profiles with incident stroke in the CHARLS cohort: A machine learning analysis.

Medicine
Using the 2011 baseline data of the China health and retirement longitudinal study, we examined the associations between serum lipids and other risk factors and incident stroke, and developed and compared multiple machine learning models for stroke-r...

Stroke Sensitivity Calculation in Medical Emergency Calls and Factors Associated With Stroke Suspicion: A Retrospective Registry-Based Study.

Annals of emergency medicine
STUDY OBJECTIVE: Sensitivity for stroke detection in emergency medical communication centers (EMCCs) varies widely. Few studies offer detailed insights into the out-of-hospital pathways of patients with stroke. This study explored the ability of EMCC...

Machine learning prediction of thrombolysis efficacy using hs-CRP and inflammatory markers in stroke.

Medicine
The aim of this study was to investigate the relationship between serum ultrasensitive C-reactive protein (hs-CRP) levels and stroke incidence and to assess its potential role in decision-making for thrombolytic therapy in stroke. Given that hs-CRP i...

`Probabilistic ensemble learning for prediction of stroke thrombectomy outcomes from the NeuroVascular Quality Initiative-Quality Outcomes Database (NVQI-QOD) Acute Ischemic Stroke Registry.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
INTRODUCTION: Mechanical Thrombectomy (MT) is the standard of care in the interventional management of Acute Ischemic Stroke (AIS). The NVQI-QOD registry records detailed patient characteristics, pre-operative imaging, procedure metrics, and post-ope...

Machine learning prediction models for stroke-associated pneumonia:Meta-analysis.

Computers in biology and medicine
OBJECTIVE: The heterogeneity of machine learning (ML) models predicting the risk of stroke-associated pneumonia (SAP) is considerable. This study aims to conduct a meta-analysis and comparison of published ML models that predict SAP risk.

Towards Automated Eye Movement Characterization for Stroke Patients Using Synthetic Video Data and Machine Learning.

Studies in health technology and informatics
Stroke is a critical medical emergency that can cause permanent disability or death. Rapid identification of stroke, especially in prehospital settings, is crucial for timely treatment. Video analysis and machine learning (ML) could facilitate the pr...

Confidence-linked and uncertainty-based staged framework for phenotype validation using large language models.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: This study develops and validates the confidence-linked and uncertainty-based staged (CLUES) framework by integrating large language models (LLMs) with uncertainty quantification to assist manual chart review while ensuring reliability th...

Associations of the Hs-CRP/HDL-C ratio with stroke among US adults: Evidence from NHANES 2015-2018.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: The high-sensitivity C-reactive protein (Hs-CRP)-to-high-density lipoprotein cholesterol (HDL-C) ratio, which integrates insights into inflammation and lipid metabolism, serves as a comprehensive indicator. The association between this ra...