AIMC Topic: Cardiovascular Diseases

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Data-driven identification of subgroups in early rheumatoid arthritis: mortality and cardiovascular disease in a cohort from western Norway.

RMD open
AIM: To identify subgroups of early rheumatoid arthritis (RA) based on comorbidities and RA manifestations and to investigate their associated risks of cardiovascular events and mortality.

Development and validation of a machine learning model for cardiovascular disease risk prediction in type 2 diabetes patients.

Scientific reports
Patients with type 2 diabetes mellitus (T2DM) have a significantly higher risk of cardiovascular disease (CVD) compared to the general population. Accurately predicting this risk is crucial for developing personalized treatment plans and public healt...

Statin-dependent and -independent pathways are associated with major adverse cardiovascular events in people with HIV.

The Journal of clinical investigation
BACKGROUNDStatin therapy lowers the risk of major adverse cardiovascular events (MACE) among people with HIV (PWH). Residual risk pathways contributing to excess MACE beyond LDL-cholesterol (LDL-C) are not well understood. Our objective was to evalua...

Artificial Intelligence Automation of Echocardiographic Measurements.

Journal of the American College of Cardiology
BACKGROUND: Accurate measurement of echocardiographic parameters is crucial for the diagnosis of cardiovascular disease and tracking of change over time; however, manual assessment requires time-consuming effort and can be imprecise. Artificial intel...

VO Max in Clinical Cardiology: Clinical Applications, Evidence Gaps, and Future Directions.

Current cardiology reports
PURPOSE OF REVIEW: VO₂ max is a fundamental marker of cardiorespiratory fitness with substantial prognostic and diagnostic value within the field of cardiology. This review analyzes current and emerging evidence regarding its clinical uses, highlight...

An intelligent diagnosis method for cardiovascular diseases based on the CNN-CBAM-GRU model.

PloS one
Early diagnosis of cardiovascular diseases (CVDs) is essential for improving patient outcomes. As a primary diagnostic modality, electrocardiogram (ECG) signals pose challenges for automatic classification due to their complex temporal and morphologi...

Phenotypic Selectivity of Artificial Intelligence-Enhanced Electrocardiography in Cardiovascular Diagnosis and Risk Prediction.

Circulation
BACKGROUND: Artificial intelligence (AI)-enhanced ECG (AI-ECG) models are often designed to detect specific anatomical and functional cardiac abnormalities. Understanding the selectivity of their phenotypic associations is essential to inform their c...

Adipose tissue gene expression and longitudinal clinical phenotypes are early biomarkers of lipid-regulating drug usage.

Scientific reports
Cardiovascular disease progression is characterised by the dysregulation of lipid metabolism and pro-atherogenic effects of adipose tissue signalling. Recent findings from the analysis of transcriptomic data in bulk tissue has enabled these insights ...

Assessment of pulse wave velocity through weighted visibility graph metrics from photoplethysmographic signals.

Scientific reports
Pulse Wave Velocity (PWV) is a widely recognized non-invasive biomarker of arterial stiffness and an independent predictor of cardiovascular risk, including atherosclerosis, hypertension, and vascular aging. Accurate, accessible estimation of PWV is,...