Strokes

Risk-Guided Screening for Atrial Fibrillation Using Electronic Health Records.

BACKGROUND: Screening for atrial fibrillation (AF) on the basis of AF risk may be more effective. We aimed to develop, externally validate, and prospectively test a machine learning prediction model using electronic health records (EHRs) to guide AF screening. METHODS: We developed and validated a random forest prediction model for new AF within 6 months, using age, sex, and 10 comorbidities (Futu...

Heterogeneity in the association between antihypertensive medications and Alzheimer's disease and related dementias risk: A multidimensional machine learning analysis to inform drug repurposing.

BackgroundAlzheimer's disease and related dementias (ADRD) place an immense burden on patients, families, and health systems in the United States. Hypertension is highly prevalent in ADRD patients, and antihypertensive medications (AHMs) may confer neuroprotective benefits. However, evidence of association between AHM use and ADRD risk remains limited, especially by drug classes and across populat...

Association Between Inflammatory Biomarkers And Carotid Ultrasound Parameters In The Northern Manhattan Stroke Study.

Inflammation contributes to atherosclerosis and vascular remodeling, but the immune pathways associated with distinct carotid ultrasound phenotypes, i...

Interpretable Dual-Stream EEG-MRI Fusion Uncovers Structure-Function Signatures of Stroke Motor Recovery.

Motor recovery prediction after stroke is hindered by the inability of single-modality imaging to capture how structural damage and functional reorgan...

Mechanics, Fracture, and Fragmentation of Thrombi: A Computational Study Review.

Thrombosis drives myocardial infarction, acute ischemic stroke and pulmonary embolism, yet more than half of patients undergoing mechanical thrombecto...

Optimising the breast radiotherapy planning pathway: a quality improvement project at a regional cancer centre.

At the South West Wales Cancer Centre, breast radiotherapy accounts for 24% of the radiotherapy workload. In 2021, only 16% of patients started treatm...

Phenotypic Clustering of Idiopathic Pulmonary Arterial Hypertension: Insights Into Pulmonary Vascular and Cardiometabolic Co-Morbidity Trajectories.

Idiopathic pulmonary arterial hypertension (IPAH) exhibits significant clinical heterogeneity, necessitating a precision medicine approach. This study...

Leveraging free-text clinical records for heart disease classification through structured feature mapping.

Hypertension and diabetes are major risk factors for heart disease, which remains among the leading causes of morbidity and mortality worldwide. Heart...

Risk Factors for Coronary Heart Disease and Stroke Among Older Adults With Metabolic Dysfunction-Associated Steatotic Liver Disease: A Nationwide Cohort Study.

BACKGROUND: Older adults with metabolic dysfunction-associated steatotic liver disease have elevated cardiovascular disease (CVD) risk, yet convention...

De Novo-Designed Peptide-Engineered Multimodal Platform for Post-Ischemic Stroke Tissue Repair.

Orchestrating tissue regeneration in complex pathologies like post-ischemic stroke requires materials that can precisely regulate multiple signaling p...

Radiation dose reduction in computed tomography perfusion of acute ischemic stroke patients using a denoising autoencoder.

BACKGROUND: Ischemic stroke results from the occlusion of a cerebral artery and is a leading cause of mortality and disability worldwide. Multimodal c...

Machine learning-based identification of cardiovascular risk modifiers in patients with very high LDL cholesterol: A cross-sectional study.

Individuals with LDL cholesterol (LDL-C) ≥ 190 mg/dL face a markedly increased risk of major adverse cardiovascular events (MACE). Traditional risk ca...

Intracardiac Echocardiography-Guided Left Atrial Appendage Occlusion: A Comprehensive Narrative Review.

Intracardiac echocardiography (ICE) is an alternative to transesophageal echocardiography for imaging guidance during left atrial appendage occlusion ...

Smartphone-Based Brunnstrom Stage Classification of Hemiparetic Gait via Skeleton-Attention-LSTM-Inception Network.

OBJECTIVE: The accurate assessment of hemiparetic gait after stroke was essential for understanding the extent of motor impairment and for guiding reh...

How can we best predict energy expenditure in preschoolers? A comparison of machine learning models, METs computation and physical activity classification.

The first objective of this study was to refine previously designed machine learning models that predict energy expenditure (EE) of preschool children...

First-pass aspiration versus stent retriever thrombectomy: machine learning study of treatment effect heterogeneity.

BACKGROUND: Randomized trials have shown equivocal outcomes between a direct aspiration as first-pass technique (ADAPT) and stent retriever (SR) strok...

Development and validation of an interpretable machine learning model for predicting hypertension risk in patients with psoriasis.

OBJECTIVE: Hypertension is a common yet frequently underdiagnosed comorbidity in psoriasis patients. Early identification and blood pressure control a...

Large-Scale Plasma Proteomics Profiles for Predicting Atrial Fibrillation Associated Stroke Risk : Type of manuscript: Original Research.

BACKGROUND: Stroke is a major complication of atrial fibrillation (AF), and risk prediction using the congestive heart failure, hypertension, age, dia...

Myocardial Native T1 Mapping in the German National Cohort (NAKO): Associations with Age, Sex, and Cardiometabolic Risk Factors.

BACKGROUND: In cardiovascular magnetic resonance (CMR), myocardial native T1 mapping enables quantitative, non-invasive tissue characterization and is...

A large-scale comparative study of YOLO-based detectors for ischemic stroke lesion localization on diffusion-weighted imaging.

Ischemic stroke lesion localization on diffusion-weighted imaging (DWI) remains challenging because acute lesions may be small, faint, irregular, or m...