Cardiovascular

Hypertension

Latest AI and machine learning research in hypertension for healthcare professionals.

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Comparative Analysis of Machine Learning Models vs. Traditional Clinical Calculators for Cardiovascular Risk Prediction

Background: Cardiovascular diseases (CVD) remain the leading global cause of mortality, responsible for approximately 31% of all deaths worldwide in 2021. Traditional risk calculators, including Framingham, ASCVD, SCORE, and SCORE2, have long constituted the cornerstone of primary prevention strategies; however, they were derived predominantly from high-income European and North American populatio...

Fusion-E2Pulse: A Multimodal Event-RGB Fusion Network for Non-contact Pulse Wave Reconstruction

Non-contact pulse wave reconstruction hinges on the precise recovery of waveform morphology, including the dicrotic notch. Conventional Red-Green-Blue (RGB)-based methods, which extract physiological signals from recorded facial videos, are constrained by the integral imaging mechanism of standard cameras, where the exposure process induces a smoothing effect that attenuates subtle vascular pulsat...

Jun 14 2026 2606.15597v1
BenDi: An Energy-Efficient Quasi-Stochastic Systolic Architecture for Edge Bioelectronics

Continuous long-term monitoring and diagnosis of biomedical signals, such as electrocardiograms (ECGs), can help mitigate an increasing threat to publ...

Jun 10 2026 2606.12235v1
DMT: Demographic Conditioning, Morphology-Enhanced Transformer for Cuffless Blood Pressure Estimation from PPG Signals

Blood pressure (BP) is a key marker for cardiovascular risk assessment and therapeutic decision-making, and Photoplethysmography (PPG) enables low-cos...

Jun 9 2026 2606.11125v1
Rationale and Design of an Artificial Intelligence Model for Diastolic Heart Failure (AID- HF): A Canadian Cardiomyopathy Collaborative (C3) Study

Diastolic heart failure (HF) in primary cardiomyopathy is under-recognized and often diagnosed late, particularly in children. While recent studies ha...

Development and validation of a dynamic risk stratification tool for predicting multidrug-resistant bacterial infections in ICU patients: A clinical prediction model and web-based calculator

Background: Multi-drug resistant Bacterial (MDRB) Infections in the intensive care units (ICUs) substantially elevate patient mortality, prolong hospi...

Patterns of Typical and Atypical Age-related Brainstem Volume losses

Background: The brainstem and its different sub-systems control essential functions such as motor agility etc. that worsen with age. The purpose of th...

MARVEL: Universal Murray's Law-informed Vessel Tree Segmentation and Topology Estimation

Vascular circulation follows fundamental biophysical principles that optimize mass transport and metabolic energy expenditure, which can be effectivel...

May 25 2026 2605.25363v1
Uncertainty Reliability Under Domain Shift: An Investigation for Data-Driven Blood Pressure Estimation in Photoplethysmography

Uncertainty quantification (UQ) is critical for safety-critical domains like healthcare, yet it is rarely evaluated under realistic out-of-distributio...

May 18 2026 2605.18008v1
A CUBS-Compatible Ultrasound Morphology and Uncertainty-Aware Baseline for Carotid Intima-Media Segmentation and Preliminary Risk Prediction

Carotid atherosclerosis is a major contributor to ischemic stroke and transient ischemic attack. Conventional ultrasound assessment is commonly based ...

May 14 2026 2605.14949v1
Estimation of Physiological Metrics from Resting ECGs Using Deep Learning in the UK Biobank, Including submaximal exercise derived VO2max, Body Fat Percentage, and Grip Strength

Maximal oxygen consumption VO2max is the gold standard for cardiorespiratory fitness but requires resource-intensive physical testing. Recent reports ...

Attractor-Vascular Coupling Theory: Formal Grounding and Empirical Validation for AAMI-Standard Cuffless Blood Pressure Estimation from Smartphone Photoplethysmography

This work proposes Attractor-Vascular Coupling Theory (AVCT), a mathematical framework showing that cardiac attractor geometry encodes blood pressure ...

May 11 2026 2605.10871v1
The German National Cohort: Ophthalmological Assessment, Baseline Profile and Potential for AI-based Eye Research

Objective: To describe the ophthalmic examination protocol within the German National Cohort (NAKO) / NAKO Gesundheitsstudie, to report the baseline p...

Prediction of Alzheimer's Disease Risk Factors from Retinal Images via Deep Learning: Development and Validation of Biologically Relevant Morphological Associations in the UK Biobank

The systemic, metabolic, lifestyle factors have established associations with Alzheimer's Disease (AD) through epidemiologic and AD-specific biomarker...

May 1 2026 2605.00665v1
Machine Learning-Assisted Feature Selection Identifies the Joint Association of Body Mass Index and Periaortic Adipose Tissue as a Risk Factor for Aortic Dissection: A Multicenter Retrospective Study

BACKGROUND: Aortic dissection (AD) is a life-threatening emergency with high mortality. Although elevated body mass index (BMI) is associated with bot...

Non-Invasive Arterial Blood Pressure Waveform Generation in Critically Ill Patients: A Sensor-Based Deep Learning Approach

Continuous monitoring of Arterial Blood Pressure (ABP) in critically ill patients requires invasive arterial catheterization, which carries risks of t...

Exposome-Based Clustering of Urinary VOC and PAH Biomarkers Reveals Racially Patterned Cardiovascular Risk in a Nationally Representative US Cohort: A Machine Learning Analysis of NHANES 2017-2018

Background Polycyclic aromatic hydrocarbons (PAHs) and volatile organic compounds (VOCs) are combustion-derived pollutants linked to cardiovascular di...

Dialysis Risk Prediction and Treatment Effect Estimation for AKI patients using Longitudinal Electronic Health Records

Progression to dialysis or end-stage renal disease is a rare but clinically important outcome. Clinicians need evidence on how medication exposures in...

Apr 27 2026 2604.24547v1
Integrative Clinical-Molecular Modeling Identifies LRRN4CL as a Determinant of Structural and Functional Myocardial Improvement

Background: Mechanical ventricular unloading and systemic circulatory support with left ventricular assist devices (LVADs) enable myocardial recovery ...

Comparison of the Expert Guidelines With Artificial Intelligence-Driven Echocardiographic Assessment of Diastolic Function

Backgound: Accurate assessment of diastolic function and left ventricular (LV) filling pressure is central to heart failure diagnosis and risk stratif...

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