Strokes

Empowering Patients and Clinicians: LLMs in Hypertension Care: A Scoping Review.

Large language models have emerged as potential tools to support hypertension care, including diagnosis, treatment decision-making, and patient education. However, evidence regarding their validity, performance, and clinical applicability remains limited. The objective is to map current applications of large language models in hypertension care, with emphasis on model optimization strategies, eval...

A Deep Neural Network for Interpreting Wearable Electrocardiogram Data in Atrial Fibrillation: Prospective Observational Diagnostic Accuracy Study.

BACKGROUND: Atrial fibrillation (AF) and atrial flutter (AFL) are common arrhythmias associated with the risk of ischemic stroke, which can be reduced with anticoagulation therapy. Thus, early diagnosis of AF and AFL is essential. However, diagnosis may be challenging due to the paroxysmal and asymptomatic nature of these arrhythmias. OBJECTIVE: Current diagnostic workflows involve time-consuming ...

Unsupervised Agglomerative Cluster Phenotyping of Young Patients With Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention.

BACKGROUND: Young patients with acute coronary syndrome (ACS) exhibit diverse demographic, clinical and angiographic characteristics. We hypothesized ...

Current evidence and future directions for prophylactic anticoagulation therapy after severe spontaneous intracerebral hemorrhage: a narrative review.

Patients with spontaneous intracerebral hemorrhage (sICH) are at high risk for venous thromboembolism (VTE), a complication strongly associated with a...

The ISLES'24 Dataset: A Multimodal Stroke Imaging Dataset with Hyperacute CT, Acute Postinterventional MRI, and 3-month Clinical Outcomes.

Stroke remains a major global health burden (1,2), although outcomes have improved substantially through imaging-guided therapy and endovascular reper...

FOSL2 regulates endothelial cell state and chromatin accessibility in systemic sclerosis pulmonary vascular remodeling.

Systemic sclerosis (SSc) is characterized by fibrosis and vasculopathy affecting the skin and internal organs, leading to multiorgan dysfunction. Inju...

Precision biomarker discovery in hypertension through explainable AI and proteomics.

Hypertension is a major global health burden and a leading driver of cardiovascular disease, yet reliable blood-based biomarkers for early disease are...

Plaque-Level Machine Learning Prediction of Intraplaque Hemorrhage in Carotid Arteries Using Computed Tomography Angiography.

BACKGROUND: Carotid artery plaques, especially those with intraplaque hemorrhage (IPH), are significant contributors to ischemic stroke. Although high...

Evaluating data heterogeneity's impact on convolutional neural network performance in medical imaging.

PURPOSE: Machine learning in medical imaging (MIML) is critical to computer-aided diagnostics. However, data heterogeneity-variation in medical data a...

Recent Near-Infrared Approaches to Cytochrome-c-Oxidase Monitoring: A Systematic Review of Instruments and Algorithms.

Broadband Near-Infrared Spectroscopy (bNIRS) has emerged as a promising technique for non-invasive monitoring of the redox state of cytochrome-c-oxida...

GRaph-based analysis for stroke prediction (GRASP): A multi-modal model for identifying first ischemic stroke in high-risk population using UK biobank.

BACKGROUND: Ischemic stroke accounts for 3.71 million deaths annually worldwide. Yet current risk prediction models demonstrate modest discrimination ...

Adaptive dual-modality neuromodulation for chronic pain and muscle dysfunction: real-world insights from the NXTSTIM™ EcoAI digital platform.

BACKGROUND: Chronic musculoskeletal pain is often inadequately managed with pharmacologic therapy. Although transcutaneous electrical nerve stimulatio...

From prediction to practice: an artificial neural network-derived risk score superior to conventional scales for predicting symptomatic intracranial haemorrhage risk after thrombolysis.

Multiparametric AI-based perfusion analysis outperforms Tmax thresholding for critically hypoperfused tissue estimation in acute ischemic stroke undergoing admission MRI.

OBJECTIVE: Perfusion imaging is used to estimate critically hypoperfused tissue in acute ischemic stroke (AIS), commonly using threshold-based methods...

Speech-based digital biomarkers for early etiological stratification of Alzheimer's disease and frontotemporal degeneration: a biomarker-confirmed prospective study.

BACKGROUND: Early differentiation between Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD) is a prerequisite for secondary preven...

Comorbidity Burden and Length of Stay After Myocardial Infarction: A Retrospective Study Using Large Language Model-Assisted Chart Abstraction in a Tertiary Cardiac Hospital.

Patients' length of stay (LOS) during admission for myocardial infarction (MI) represents a closely tracked outcome metric for Cardiology services, wh...

Association of initial core volume on non-contrast CT using a deep learning algorithm with clinical outcomes in acute ischemic stroke: a potential tool for selection and prognosis?

BACKGROUND: In an extended time window, contrast-based neuroimaging is valuable for treatment selection or prognosis in patients with stroke undergoin...

Integrated Transcriptomics and Machine Learning Reveal Lipid Metabolism Related Genes in Ischemic Stroke.

Predicting post-stroke functional outcome using explainable machine learning and integrated data.

Functional outcome after acute ischemic stroke (AIS) varies widely, and existing prognostic scores may not capture complex relationships. We evaluated...

Malignant Cerebral Edema after Large-Core Anterior Circulation Stroke in the Thrombectomy Era: Prediction and Neurocritical Care Pathways.

Large-core anterior circulation ischemic stroke (LCIS) complicated by malignant cerebral edema (MCE) remains a leading cause of early death and profou...