Congestive Heart Failure

Research progress and clinical utility of multi-parameter orbital MRI in thyroid-associated ophthalmopathy.

Thyroid-associated ophthalmopathy (TAO), the most common orbital disease in adults, is a specific au...

Integrating AI-ECG and point-of-care cardiac ultrasound for screening structural heart disease: A proof-of-concept study.

BACKGROUND: Early structural heart disease (SHD) detection is crucial for improving prognostic outco...

Utilizing machine learning in echocardiographic analysis to distinguish obstructive and non-obstructive coronary artery disease.

BACKGROUND: Research on echocardiographic prognostication in non-obstructive coronary artery disease...

Development and validation of a machine learning model to predict functional outcomes in patients with recent small subcortical infarction.

OBJECTIVE: A substantial proportion of patients (12 %-25 %) with recent small subcortical infarction...

Predicting postoperative length of stay: a feature selection approach to predictive modeling in lumbar fusion surgery.

BACKGROUND: Predictive modeling has the potential to improve preoperative planning and resource allo...

Exploring Patients' Profiles Associated With the Resolution of Acute Calcium Pyrophosphate Arthritis Treated With Colchicine and Prednisone: Post Hoc Analysis of a Randomized Controlled Trial.

OBJECTIVE: The objective was to identify factors determining acute arthritis resolution and safety w...

Challenges in the diagnosis and management of hypertrophic cardiomyopathy and the promise of artificial intelligence.

Hypertrophic cardiomyopathy (HCM), the most prevalent inherited cardiomyopathy, is characterized by ...

Analysis of PANoptosis-related genes in septic cardiomyopathy by bioinformatics, machine learning and experimental validation.

The mechanisms underlying the pathogenesis of septic cardiomyopathy (SCM) are intricate and incomple...

Reproducibility of echocardiographic measurements of left ventricular systolic function: a systematic review and meta-analysis comparing artificial intelligence and clinician estimates.

Echocardiography underpins the diagnosis and management of cardiovascular disease, yet measurement v...

Value of Multiomics Over Clinical Risk Factors in Hypertension Prediction.

BACKGROUND: Several omics methods have been successfully used in hypertension prediction. However, t...

Explainable machine learning-driven predictive modelling of incident cognitive impairment in individuals with early-stage cardiovascular-kidney-metabolic syndrome: Insights from a longitudinal CHARLS cohort study.

AIMS: While cardiovascular-kidney-metabolic (CKM) syndrome has been recognised as a continuum of int...

Quantitative CT of emphysema, wall thickness and mucus plugs in alpha-1-antitrypsin deficiency: relationship to clinical outcomes.

OBJECTIVES: Alpha-1-antitrypsin deficiency (AATD) is a rare genetic disorder leading to chronic obst...

Predictors of glycemic control with imeglimin for type 2 diabetes: Results of machine learning analyses using clinical trial data.

INTRODUCTION: Identifying patient characteristics predictive of treatment response is crucial for op...

Trajectories in renal perfusion pressure during hemodynamically guided therapy are associated with worsening renal function and patient outcomes.

BACKGROUND: Worsening renal function (WRF) during acute decompensated heart failure (ADHF) therapy p...

Prediction of IDH-mutation and 1p19q-codeletion status in adult-type diffuse gliomas using three-class radiomics models.

PURPOSE: To predict the genetic subtypes of adult-type diffuse gliomas with three-class MRI radiomic...

Fully Automated Plane Prescription in Cardiac MRI: A Prospective Cohort Study.

BACKGROUND: Accurate plane positioning is important for high-quality cardiac MRI images but requires...

The evolving landscape of screening, management and treatment strategies of aortic stenosis in ATTR amyloidosis.

Transthyretin amyloid cardiomyopathy (ATTR-CM) and aortic stenosis (AS) frequently coexist in elderl...

Personalized adrenal gland volume reference ranges and development of a fully automated deep learning screening tool.

OBJECTIVE: This study aims to develop a low-dose CT-based, fully automated deep learning tool for sc...

Machine Learning-Based Prediction of Postoperative Vasoplegia After Cardiac Surgery.

OBJECTIVE: To develop and internally validate a machine-learning model for the early prediction of p...

Development and validation of a machine learning model to predict 30-day mortality in ischemic stroke patients with consciousness impairment: Insights from MIMIC-IV database and multicenter ICU data in China.

BACKGROUND: Patients with ischemic stroke complicated by consciousness disorders remain associated w...

The artificial intelligence-derived electrocardiographic age gap is associated with adverse clinical outcomes in LMNA-related cardiomyopathy.