Congestive Heart Failure

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.

Using Artificial Intelligence to Adjudicate Major Adverse Cardiovascular Events in Clinical Trials.

BACKGROUND: Major adverse cardiovascular events (MACE)-cardiovascular (CV) death, nonfatal myocardia...

Predicting Heart Failure From 12-Lead ECGs Using AI: A HeartShare/AMP-HF Pooled Cohort Analysis.

BACKGROUND: Artificial intelligence applied to electrocardiograms (ECG-AI) offers a scalable approac...

Development and Deployment of a Machine Learning Model to Triage the Use of Prostate MRI (ProMT-ML) in Patients With Suspected Prostate Cancer.

BACKGROUND: Access to prostate MRI remains limited due to resource constraints and the need for expe...

Takotsubo cardiomyopathy: Advances in pathophysiology, diagnostic biomarkers, genetic insights, multisystemic involvement, treatment updates & multidisciplinary interventions.

BACKGROUND: Takotsubo cardiomyopathy (TTC) is an acute, reversible cardiac syndrome triggered by phy...

Automated detection of neonatal pulmonary hypertension in echocardiograms with a deep learning model.

BACKGROUND: In infants, pulmonary hypertension (PH) increases morbidity and mortality. Echocardiogra...

Enhancing risk stratification for incident systolic heart failure through machine learning and natural language processing.

BACKGROUND: Clinical guidelines advocate use of validated risk models in patients experiencing heart...

Role of Multimodality Imaging in the Evaluation and Management of Cardiomyopathy and Heart Failure.

Cardiomyopathies and heart failure (HF) represent a diverse group of cardiac conditions that signifi...

How do experts classify sepsis cases for sepsis surveillance? Lessons learned from a Behavioural Artificial Intelligence Technology (BAIT) approach.

OBJECTIVES: To identify relevant objective variables for retrospective identification of 'suspected ...

BM3D filtering with Ensemble Hilbert-Huang Transform and spiking neural networks for cardiomegaly detection in chest radiographs.

Cardiomyopathy is a life-threatening condition associated with heart failure, arrhythmias, thromboem...

Identification and Verification of SLC6A15 Involved in Keloid via Bioinformatics Analysis and Machine Learning.

Keloid is a fibroproliferative disorder that poses a challenge in clinical management. This study ai...

Novel deep learning framework for simultaneous assessment of left ventricular mass and longitudinal strain: clinical feasibility and validation in patients with hypertrophic cardiomyopathy.

BACKGROUND: This study aims to present the Segmentation-based Myocardial Advanced Refinement Trackin...

Inflammatory, fibrotic and endothelial biomarker profiles in COVID-19 patients during and following hospitalization.

Survivors of severe COVID-19 often suffer from long-term respiratory issues, but the molecular drive...

Inter-AI Agreement in Measuring Cine MRI-Derived Cardiac Function and Motion Patterns: A Pilot Study.

Manually analyzing a series of MRI images to obtain information about the heart's motion is a time-c...

Artificial intelligence in cardiac sarcoidosis: ECG, Echo, CPET and MRI.

PURPOSE OF REVIEW: Cardiac sarcoidosis is a form of inflammatory cardiomyopathy that varies in its c...

Association between prenatal exposure to per- and polyfluoroalkyl substances and blood pressure among preschool-aged children: The moderating effect of child-age and the mediating effect of inflammatory cytokine.

Our aim is to evaluate the association of prenatal exposure to per- and polyfluoroalkyl substances (...

Evaluating the Performance and Potential Bias of Predictive Models for Detection of Transthyretin Cardiac Amyloidosis.

BACKGROUND: Delays in the diagnosis of transthyretin amyloid cardiomyopathy (ATTR-CM) contribute to ...

5-Hydroxymethylcytosine signatures as diagnostic biomarkers for septic cardiomyopathy.

At present, there are currently no molecular biomarkers for the early diagnosis of sepsis cardiomyop...