Hypertension

Artificial intelligence for the assessment of diastolic function.

PURPOSE OF REVIEW: Assessment of left ventricular diastolic function remains one of the most challenging aspects of echocardiography. Artificial intelligence (AI) has emerged as a transformative tool capable of automating data acquisition, analysis, and interpretation. This review summarizes recent advances in the use of AI to facilitate diastolic function assessment. RECENT FINDINGS: An increasin...

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 are critical to improving outcomes. Although machine learning (ML) is widely used in disease prediction, a model for hypertension risk within the psoriasis population remains unavailable. This study aims to develop and validate such a model in patient...

Integrated machine learning and structural bioinformatics guided identification of novel molecular scaffolds as renin inhibitors.

Cardiovascular diseases (CVDs) remain the leading cause of death globally, with hypertension as its critical hallmark. The Renin-Angiotensin-Aldostero...

Identifying treatment-responsive patient subgroups in a neutral clinical trial of Intensive blood pressure reduction in acute intracerebral hemorrhage: A post hoc explainable machine learning analysis.

The Antihypertensive Treatment of Acute Cerebral Hemorrhage (ATACH-2) trial reported no overall benefit from intensive blood pressure (BP) reduction i...

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...

Machine Learning in Diastolic Function: From Classification to Context-Aware Decision Support.

Hypertension-associated DNA methylation signatures and multi-generational epigenetic clocks in Korean adults.

Hypertension is a hallmark of vascular aging; however, the epigenetic link between biological aging and blood pressure remains unclear. This epigenome...

Effect of cataracts on systemic factor prediction from fundus images.

OBJECTIVE: To evaluate the effect of cataracts on systemic factor predictions from fundus images by comparing predictive values before and after catar...

Interpretable Machine Learning Model for Predicting Sepsis and Septic Shock Among Patients with Documented Fever at Emergency Department Triage Using Patients' Historical Data.

This study aimed to develop an interpretable machine learning-based scoring system for predicting sepsis and septic shock among febrile patients at em...

Atrial Fibrillation in Patients With Myocardial Infarction: Global Burden, Predictors, and Prognostic Impact.

Atrial fibrillation (AF) is the most prevalent sustained arrhythmia worldwide. Acute myocardial infarction (AMI) is closely intertwined with AF throug...

Interpretable machine learning for cardiovascular disease risk prediction in cancer survivors: development and internal validation.

BACKGROUND: Cardiovascular disease (CVD) is a major concern among cancer survivors. However, the intersection of cancer and CVD has only recently gain...

Explainable machine learning model for early prediction of ICU death in chronic heart failure with pulmonary infection.

OBJECTIVE: To develop and validate a machine learning model for predicting ICU mortality in CHF patients with pulmonary infection. METHODS: Clinical d...

Age-Related Brain Atrophy Mediates a Composite Outcome of One-Year Ischemic Stroke Recurrence and All-Cause Mortality Through YKL-40-Related Inflammatory Pathways: A Structural Equation Model.

Chronological age is a strong predictor of poor outcomes after ischemic stroke but may not fully capture underlying biological vulnerability. This stu...

An explainable real-time artificial intelligence -assisted system to reduce intradialytic hypotension.

BACKGROUND: Intradialytic hypotension (IDH) is a frequent complication in hemodialysis and is associated with adverse cardiovascular and neurological ...

Clinical applications of artificial intelligence in hypertension management: current evidence and future perspectives.

BACKGROUND: Hypertension remains the leading modifiable risk factor for cardiovascular morbidity and mortality worldwide, with persistently inadequate...

Understanding HFpEF Through Imaging: Strengths, Limitations, and Current State of the Art.

Heart failure with preserved ejection fraction (HFpEF) is a clinical syndrome characterized by dyspnea caused by hemodynamic congestion, which develop...

Development and internal validation of an interpretable machine learning model using routine laboratory data for systemic sclerosis-associated pulmonary arterial hypertension.

This study aimed to develop and validate an interpretable machine learning (ML) model using routine laboratory data to support clinical decision-makin...

Personalised approach to hypertension treatment: protocol for the HYPERMARKER randomised controlled trial.

INTRODUCTION: Blood pressure treatment response is variable in individual patients, and the choice of medical therapy is often dependent on clinician ...

Machine learning-driven integration of 24-hour ambulatory blood pressure and its variability.

Twenty-four hour ambulatory blood pressure (BP) monitoring (24-hour ABPM) is considered the best out-of-office BP measurement to assess hypertension. ...

Machine learning prediction of physician-assigned treatment categories from pre-procedural electronic medical record data in cardiac patients: A multiclass classification study.

Cardiovascular diseases (CVDs) remain a leading source of morbidity, mortality, and healthcare burden worldwide. In patients with coronary artery dise...