Strokes

Association between non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and the characteristics of carotid artery plaques: a retrospective study and machine learning model construction.

BACKGROUND: Low-echo plaques are closely related to stroke. Non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) is a novel lipid metabolism indicator. This study aims to evaluate the predictive value of NHHR for identifying vulnerable plaques. METHODS: This study retrospectively collected data from 3,339 patients with carotid plaque. We used multivariable ...

GaitNet: Transfer Learning-Enhanced CNN-GRU Architecture for Intention Detection in Healthy and Post-Stroke Participants.

Highly accurate, data-efficient, and real-time detection of human motion intention is essential for the effective control of assistive and rehabilitation robots in post-stroke recovery. However, existing approaches focused on healthy participants and often require large amounts of subject-specific data, limiting their clinical applicability. To address these challenges, we propose GaitNet, a novel...

Objective dyspnea measurement in real time using a forehead wearable and artificial intelligence.

Dyspnea is a complex symptom measured using subjective patient-reported ratings. Continuous, automated dyspnea measurements are needed, especially in ...

Machine learning based prediction models for first stroke in community primary care: a systematic review and meta-analysis.

BACKGROUND: Stroke is the third leading cause of death and the fourth leading cause of disability globally, particularly in low- and middle-income cou...

Wearable devices for atrial fibrillation: diagnostic and screening roles of ECG and PPG-A systematic review.

OBJECTIVE: Atrial fibrillation (AF) is a major predictor of heart failure, stroke, and mortality. Traditional Holter monitors and event recorders are ...

Dual-Module Near-Infrared Fluorophores Discovery System via Knowledge Transfer.

In vivo near-infrared (NIR) imaging is an emerging technique in biomedical research. It is particularly important for examining living tissue owing to...

Age-related metabolomic signatures and stroke susceptibility in a population-based cohort.

Aging-related metabolic dysregulation and vascular vulnerability contribute substantially to stroke susceptibility, yet subtype-specific metabolic sig...

Left Ventricular Thrombus in Ischemic Heart Failure: Machine-learning-based Prediction of Six-month Persistence and One-year Outcomes.

Left ventricular thrombus (LVT) in ischemic heart failure carries embolic risk; tools to anticipate persistence are limited. We studied 190 consecutiv...

EMBC Special Issue: Non-invasive BP Estimation via Carotid-Brachial-Radial Coupling: A Physics-Informed Asymmetric Cycle Network Approach.

Photoplethysmogram (PPG) based cuffless blood pressure (BP) monitoring holds significant potential to revolutionize hypertension management. However, ...

Low-intensity transcranial ultrasound stimulation improves motor behavior and modulates cortical functional network connectivity in mice with ischemic stroke.

The recovery of motor function in patients with ischemic stroke is closely related to the plastic remodeling of cortical functional networks. Low-inte...

An interpretable combinatorial data-mining framework for predicting new-onset hypertension in the general population.

We previously established an interpretable combinatorial data-mining framework to identify combinations of clinical factors predictive of heart failur...

Burden trajectories of stroke attributable to lipid-glucose dysfunction and biomarker validation: evidence from the global burden of disease (GBD) 2023 and the China health and retirement longitudinal study (CHARLS).

BACKGROUND: Metabolic dysfunction is an important contributor to stroke burden and may also help identify individuals at higher future risk of stroke....

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study.

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage increases risk of vascular events...

Machine learning-based prediction model for long-term mortality after ischemic stroke.

Stroke, a leading cause of death, requires precise predictions of life expectancy. Traditional scores focused on short-term outcomes and required labo...

Phenotyping of pulmonary arterial hypertension associated with congenital heart disease using latent class analysis: insights from a national prospective registry.

BACKGROUND: Pulmonary arterial hypertension associated with congenital heart disease (PAH-CHD) is characterized by substantial prognostic and therapeu...

Identifying Patients at Elevated Risk of Stroke After.

BACKGROUND: Transcarotid artery revascularization (TCAR) has assumed a significant role in the surgical treatment of extracranial carotid occlusive di...

Circulating acidic α-glucosidase as a potential biomarker for lactate-related immunometabolism in ischemic stroke.

BACKGROUND: The role of lactate metabolism in ischemic stroke (IS) remains incompletely understood. This study aimed to characterize lactate-related t...

A machine learning-based framework for predicting hypertension using serum hematological factors.

Hypertension (HTN) is a leading global cause of cardiovascular disease (CVD) and all-cause mortality, underscoring the need for early detection and in...

Artificial intelligence (AI)-powered diagnostic support for stroke via Telegram bot: preliminary findings.

BACKGROUND: Annually, stroke affects over 15 million people globally. Early intervention is critical in the management of stroke. However, the "golden...

Retinal Microvascular Signatures as Early Predictors of Cardiovascular Risk: Integrating Pathophysiology, Molecular Insights, and Artificial Intelligence.

Cardiovascular diseases (CVDs) continue to be a significant public health burden and public health emergency in the world, underscoring the importance...