Congestive Heart Failure

Improving transthyretin cardiac amyloidosis detection from electrocardiograms through the Willem artificial intelligence platform.

BACKGROUND: Transthyretin amyloid cardiomyopathy (ATTR-CM) is a frequently underdiagnosed disease in...

Annular Prior Prompt Learning for Medical Images Segmentation.

Excellent performance has been achieved on medical image segmentation. Still, existing algorithms pe...

Feasibility of Free-breathing Deep Learning-reconstructed Single-Shot Cine MRI in Participants with Arrhythmia: Comparison with Conventional Segmented Cine MRI.

Purpose To evaluate the feasibility of retrospective electrocardiographically (ECG) gated single-sho...

Pre-heart failure in early chronic kidney disease: clinical epidemiology and treatment.

Chronic kidney disease (CKD), defined per the Kidney Disease: Improving Global Outcomes (KDIGO) guid...

Multi-label Ensemble Model for Knee Joint Anatomy and Lesion Segmentation: Segmentation of Clinical Images With Ensembling, Morphology, and Attention (SCEMA).

PURPOSE: Quantitative MRI analysis holds significant promise for improving the early diagnosis and p...

Predictive accuracy of a perioperative hemodynamic indices-based prediction model for moderate-to-severe acute kidney injury after orthotopic heart transplantation.

BACKGROUND: Acute kidney injury is a common complication after orthotopic heart transplantation. Pre...

Assessing the Predictive Value of Kolmogorov-Arnold Networks for the No-Reflow Phenomenon in ST-Segment Elevation Myocardial Infarction: A Comparative Machine Learning Study.

OBJECTIVE: The no-reflow phenomenon in ST-segment elevation myocardial infarction (STEMI) is a signi...

Multi-scale adaptive fusion network for retinal layer and fluid segmentation in optical coherence tomography B-scans.

Major treats to visual health includes diabetic macular edema (DME), age-related macular degeneratio...

Using machine learning algorithms to predict MACE in peritoneal dialysis patients.

The study aimed to predict the risks of Major adverse cardiac events (MACE) in patients undergoing p...

Emerging perspectives in cardiovascular medicine.

Cardiovascular medicine continues to evolve rapidly through advances in molecular biology, biomarker...

Construction and validation of high altitude pulmonary edema prediction models based on deep learning and quantitative analysis of X-ray images.

Reappraising cardiac function with myocardial contraction fraction: normal values, disease detection, and prognostication.

AIMS: Assessing cardiac function is critical for managing cardiovascular disease, guiding treatment,...

A machine learning approach using echocardiographic and hematological parameters to classify cerebral small vessel disease burden.

BACKGROUND: Cerebral small vessel disease (CSVD) is a leading cause of stroke and dementia and is as...

Addressing disparities in transthyretin amyloid cardiomyopathy: A systematic review of artificial intelligence in the early identification to improve patient outcomes.

BACKGROUND: Transthyretin amyloid cardiomyopathy (ATTR-CM) remains substantially underdiagnosed amon...

Effect of SnapShot Freeze 2 on Reducing Pulsation Artifacts in Coronary Artery Imaging of Patients With High Heart Rates.

BACKGROUND This study aimed to evaluate the effect of SnapShot Freeze 2 (SSF2) on reducing pulsation...

Machine-learning approach on echocardiography to improve the detection of transthyretin amyloid cardiomyopathy: GRAAL algorithm.

AIMS: Transthyretin amyloid cardiomyopathy (ATTR-CM) is an increasingly recognized cause of heart fa...

A generalizable deep learning system for cardiac MRI.

Cardiac MRI allows for a comprehensive assessment of myocardial structure, function and tissue chara...

Enhancing few-shot personalized cuffless blood pressure estimation with self-supervised learning.

Objective.Individual differences across subjects reduce the accuracy of physiological signal-based c...

Chronic heart failure detection based on long-term RR interval dynamics.

Chronic heart failure (CHF) is a condition affecting millions worldwide, characterized by the heart'...

Imaging biomarkers of post-COVID dyspnea: insights from machine learning CT patterns and parametric response mapping.

Cardiopulmonary exercise testing in contemporary cardiology: physiological insights, novel applications and evolving algorithms.

Cardiopulmonary exercise testing (CPET) allows for the study of the pathophysiology of exercise into...