Congestive Heart Failure

Predicting blood pressure without a cuff using a unique multi-modal wearable device and machine learning algorithm.

Blood pressure is a critical risk factor for cardiovascular diseases (CVDs), yet most adults do not monitor it frequently enough to prevent serious complications. This is in part because the traditional cuff-based method is inconvenient, uncomfortable, and does not allow for continuous monitoring. To address these constraints, we developed a unique multi-modal wearable device and used a random for...

Computerized Modeling of Electrophysiology and Pathoelectrophysiology of the Atria -- How Much Detail is Needed?

This review focuses on the computerized modeling of the electrophysiology of the human atria, emphasizing the simulation of common arrhythmias such as atrial flutter (AFlut) and atrial fibrillation (AFib). Which components of the model are necessary to accurately model arrhythmogenic tissue modifications, including remodeling, cardiomyopathy, and fibrosis, to ensure reliable simulations? The cen...

Artificial Intelligence Tools for Preconception Cardiomyopathy Screening Among Women of Reproductive Age.

PURPOSE: Identifying cardiovascular disease before conception and in early pregnancy can better inform obstetric cardiovascular care. Our main objecti...

4D-CTA Image and geometry dataset for kinematic analysis of abdominal aortic aneurysms

This article presents a dataset used in the article "Kinematics of Abdominal Aortic Aneurysms", published in the Journal of Biomechanics. The datase...

4D-CTA Image and geometry dataset for kinematic analysis of abdominal aortic aneurysms

This article presents a dataset used in the article "Kinematics of Abdominal Aortic Aneurysms" [arXiv:2405.13377], published in the Journal of Biome...

Predicting cardiovascular risk with hybrid ensemble learning and explainable AI.

Cardiovascular diseases (CVDs) are still one of the leading causes of death globally, underscoring the importance of early and right risk prediction f...

Self-supervised model-informed deep learning for low-SNR SS-OCT domain transformation.

This article introduces a novel deep-learning based framework, Super-resolution/Denoising network (SDNet), for simultaneous denoising and super-resolu...

Triple cardiovascular disease detection with an artificial intelligence-enabled stethoscope (TRICORDER): design and rationale for a decentralised, real-world cluster-randomised controlled trial and implementation study.

INTRODUCTION: Early detection of cardiovascular disease in primary care is a public health priority, for which the clinical and cost-effectiveness of ...

Predicting Risk of Pulmonary Fibrosis Formation in PASC Patients

While the acute phase of the COVID-19 pandemic has subsided, its long-term effects persist through Post-Acute Sequelae of COVID-19 (PASC), commonly ...

Leveraging Vision Transformers in Multimodal Models for Retinal OCT Analysis.

Optical Coherence Tomography (OCT) has become an indispensable imaging modality in ophthalmology, providing high-resolution cross-sectional images of ...

Deep Learning-Based Chronic Obstructive Pulmonary Disease Exacerbation Prediction Using Flow-Volume and Volume-Time Curve Imaging: Retrospective Cohort Study.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a common and progressive respiratory condition characterized by persistent airflow limitat...

Boi-Ogi-To, a Traditional Japanese Kampo Medicine, Promotes Cellular Excretion of Chloride and Water by Activating Volume-Sensitive Outwardly Rectifying Anion Channels.

The Japanese Kampo medicine Boi-ogi-to (BOT) is known as an effective therapeutic agent for edema and nephrosis by promoting the excretion of excess b...

Detection of Hypertrophic Cardiomyopathy on Electrocardiogram Using Artificial Intelligence.

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is associated with significant morbidity and mortality, including sudden cardiac death in the young. Its...

Integrating Dynamic Red Blood Cell Distribution Width Monitoring and β-Blocker Therapy for Mortality Prediction in Intensive Care Unit Cardiomyopathy Patients: A Bayesian Multivariate Joint Model and Machine Learning Study.

Cardiomyopathy is a key cause of cardiovascular mortality in critically ill patients. Although red blood cell distribution width (RDW) is recognized ...

Hybrid Deep Learning for Survival Prediction in Brain Metastases Using Multimodal MRI and Clinical Data.

Survival prediction in patients with brain metastases remains a major clinical challenge, where timely and individualized prognostic estimates are cr...

A novel approach for ECG signal classification using sliding Euclidean quantization and bitwise pattern encoding.

This study aims to introduce a novel, computationally lightweight feature extraction technique called Sliding Euclidean Pattern Quantization (SEPQ), w...

An MRI-based deep transfer learning radiomics nomogram for predicting meningioma grade.

The aim of this study was to establish a nomogram based on clinical, radiomics, and deep transfer learning (DTL) features to predict meningioma grade....

Investigating the correlation between smoking and blood pressure via photoplethysmography.

Smoking has been widely identified for its detrimental effects on human health, particularly on the cardiovascular health. The prediction of these eff...

The Accuracy of ChatGPT-4o in Interpreting Chest and Abdominal X-Ray Images.

Large language models (LLMs), such as ChatGPT, have emerged as potential clinical support tools to enhance precision in personalized patient care, bu...

Atrial Cardiomyopathy in Atrial Fibrillation: A Multimodal Diagnostic Framework.

Atrial fibrillation (AF) is increasingly recognized as the clinical manifestation of an underlying atrial disease process rather than a purely electri...