Congestive Heart Failure

Generalization of Left Ventricular Segmentation Models to LVNC Patients: A Comparative Study.

Left ventricular non-compaction (LVNC) is a rare cardiomyopathy with distinctive myocardial morpholo...

Preoperative frailty for predicting in-hospital mortality in patients after cardiac surgery: an interpretable Machine learning model based on a retrospective multicenter cohort study.

BACKGROUND AND OBJECTIVE: Accurate prediction of mortality risk after cardiac surgery is crucial for...

Machine learning-based risk stratification identifies heart failure with preserved ejection fraction as an independent predictor of adverse outcomes in hypertrophic cardiomyopathy.

Heart failure with preserved ejection fraction (HFpEF) is increasingly recognized in hypertrophic ca...

Prospective Data Curation Enables High-Performance Artificial Intelligence for Diabetic Retinopathy Screening in a Resource-Limited Setting.

PURPOSE: To determine whether a high-quality, prospectively curated dataset can, by itself, enable t...

Malignant Cerebral Edema after Large-Core Anterior Circulation Stroke in the Thrombectomy Era: Prediction and Neurocritical Care Pathways.

Large-core anterior circulation ischemic stroke (LCIS) complicated by malignant cerebral edema (MCE)...

Decision support systems (DSS) for predicting hypertensive events using real-world telemonitoring data.

OBJECTIVE: This study contributes to the limited literature on applying machine learning (ML) to tel...

Automatic monitoring of single-wall MAPSE by transesophageal echocardiography for tracking global left ventricular function irrespective of regional hypokinesia: a secondary analysis.

BACKGROUND: Measuring mitral annular plane systolic excursion (MAPSE) serially in a single wall may ...

A novel signal distribution-based approach to characterize atrial cardiomyopathy.

A machine learning approach to predicting dyspnea with noninvasive biomarkers.

Dyspnea is the subjective sensation of breathing discomfort. This symptom is highly prevalent in pat...

Deep learning based eye disease classification using Optical Coherence Tomography (OCT) images.

BACKGROUND AND OBJECTIVE: Optical Coherence Tomography (OCT) imaging plays a crucial role in the ear...

Computed tomography in ARDS, from morphological insights to AI-powered multi-modal analysis: a narrative review.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a critical clinical condition characterize...

Robotic-assisted biventricular durable assist device implantation: The first in human experience.

We report a novel approach of robotic-assisted, minimally invasive biventricular assist device (BiVA...

Objective prediction of siesta based on machine learning and association with obesity.

OBJECTIVES: To predict siesta behavior using machine learning models trained on self-reported and ob...

Effect of a mobile health intervention optimised with artificial intelligence on blood pressure and other cardiovascular risk factors in adults with high blood pressure: rationale and design of My Intelligent Cardiac Assistant (MICArdiac) randomised controlled trial.

INTRODUCTION: Control of blood pressure (BP) continues to be a challenge globally. Clinical trials h...

DIA-PINN. A physics-informed machine learning method to estimate global intrinsic diastolic chamber properties of the left ventricle from pressure-volume data.

Background: Pressure-volume (PV) loop analysis remains the gold standard for assessing the intrinsic...

Personalized artificial intelligence based left ventricular ejection fraction and systolic dysfunction assessment.

Left-ventricular (LV) ejection fraction (LVEF) is a fundamental measure of cardiac function, typical...

Enhancing prediabetes and diabetes detection through a machine learning-enabled self-assessment approach.

OBJECTIVES: Reliable, accessible, noninvasive self-assessment screening for prediabetes/diabetes is ...

Determinants of LV Myocardial Dyssynchrony in CHF: Impact of Mechanical and Electrical Dyssynchrony.

Chronic heart failure (CHF) patients often present with heterogeneous patterns of cardiac dyssynchro...

Artificial intelligence-based detection of acute postoperative airway complications following anterior cervical spine surgery: a retrospective imaging evaluation.

STUDY DESIGN: Retrospective imaging evaluation using an artificial intelligence (AI)-generated model...

Artificial Intelligence-Enabled Prediction of Reversible Versus Irreversible Chemotherapy-Induced Myocardial Injury: Toward Precision Cardio-Oncology.

Cancer therapy-related cardiac dysfunction remains a major cause of morbidity among cancer survivors...

A novel machine learning model of smartphone-based 1-minute sit-to-stand test for prediction of six-minute walk test distance in patients with COPD.

BACKGROUND: Regular assessment of exercise tolerance is essential for managing COPD, nevertheless, t...