Congestive Heart Failure

Clinical Evaluation of A-LIKNet: Deep Learning-accelerated Single-breath-hold CINE Magnetic Resonance Imaging for Cardiac Function Assessment.

OBJECTIVES: To evaluate the diagnostic accuracy and quantitative agreement of A-LIKNet (attention-incorporated network for sharing low-rank, image, and k-space information) deep learning (DL)-accelerated 2D cardiac CINE MRI acquired in a single breath-hold, compared with standard multi-breath-hold CINE sequences, for assessing biventricular volumes and function. MATERIALS AND METHODS: In this sing...

Pinoresinol diglucoside from Eucommia ulmoides attenuates diabetic cardiomyopathy through suppressing the store-operated calcium entry and downregulating the STIM1/Orai1/NFAT3 signaling pathway.

Pinoresinol diglucoside (PDG), an active component derived from Eucommia ulmoides, exhibits therapeutic effects against apoptosis, inflammation, and hypertrophy, etc. However, whether PDG plays a protective role in diabetic cardiomyopathy (DCM) is not fully elucidated. This study aimed to investigate the role and potential mechanism of PDG in DCM. The possible mechanism of PDG targeting DCM was id...

Multi-Center Adversarial Bi-Phase Cross-Attention Network for Right Ventricular Segmentation and Functional Classification in Echocardiography.

BACKGROUND: Automated right ventricular (RV) analysis in 2D echocardiography is limited by the morphological complexity of RV segmentation and the dom...

Comparative machine learning approaches to prognosticate clinical outcomes in oral and maxillofacial space infections: a retrospective analysis.

BACKGROUND: The objective of this study was to evaluate the performance of multiple machine learning algorithms to provide evidence supporting early i...

Prognostic models for diabetic kidney disease outcomes: A systematic review.

OBJECTIVE: This systematic review aimed to systematically evaluate the methodological quality and predictive performance of existing prognostic models...

Temporal deep learning for 28-day mortality prediction in critically ill ovarian cancer patients: a multicenter development and validation study using hourly vital signs.

BACKGROUND: Ovarian cancer patients requiring intensive care unit (ICU) admission face particularly grave prognosis, yet current prognostic models rel...

Echocardiographic assessment in arterial hypertension: a contemporary narrative review.

Arterial hypertension remains the leading modifiable cause of cardiovascular morbidity and mortality resulting in characteristic changes in cardiac st...

Predictive Model for Thrombosis in Mature Autologous Arteriovenous Fistula.

OBJECTIVE: Based on the "high-risk stenosis-thrombosis" theory, this study developed a risk prediction model for thrombosis in mature autogenous arter...

Deep learning-based effusion-synovitis volume measured on MRI is associated with osteoarthritis progression: A longitudinal analysis of data from the osteoarthritis initiative.

OBJECTIVE: To investigate whether the 48-month change in effusion-synovitis volume (ΔESV) is associated with concurrent knee osteoarthritis progressio...

Decoding the Complexity of Tricuspid Regurgitation Prognostic Drivers Using Explainable Artificial Intelligence.

AIMS: Prognosis in tricuspid regurgitation (TR) is shaped by complex clinical and hemodynamic interactions, complicating risk stratification. We aimed...

Artificial intelligence-enhanced nurse navigation for monitoring and care of long COVID.

INTRODUCTION: Long COVID is a multisystem condition with challenging diagnosis. Nurse-navigation, a patient-centered intervention, can enhance educati...

Development and external validation of an interpretable machine learning model for predicting prolonged postoperative ICU length of stay in coronary artery bypass grafting patients using MIMIC-IV 3.1 and eICU-CRD 2.0.

BACKGROUND: Prolonged postoperative intensive care unit (ICU) length of stay (LOS) after coronary artery bypass grafting (CABG) drives resource use ye...

Retinal vascular parameters as AI-driven biomarkers for pulse wave velocity assessment: a telemedicine strategy for cardiovascular risk assessment.

BACKGROUND: Pulse wave velocity (PWV), known as the gold standard for evaluating arterial stiffness, is limited by device dependence. This study aims ...

The diagnostic and predictive value of AI-combined multilayer spiral CT for MACE after emergency PCI in STEMI patients: A prospective cohort study.

ST-segment elevation myocardial infarction (STEMI) patients remain at substantial risk for major adverse cardiovascular events (MACE) following emerge...

A Machine-Learning Model for Accurate Diuresis Prediction in Acute Heart Failure (DRC-AHF).

AIMS: We aimed to develop a machine learning-based tool for accurate quantitative prediction of diuretic response in acute heart failure (AHF). METHOD...

NOX4 promotes cardiomyocyte ferroptosis-related injury in septic cardiomyopathy in associated with mitochondrial dysfunction and impaired NRF2 nuclear translocation.

Septic cardiomyopathy is a common early complication of sepsis, and its underlying mechanisms remain incompletely understood. In this study, we integr...

First-Pass Reperfusion After Endovascular Thrombectomy: A Real-World Analysis with Explainable Machine Learning for Intra-Procedural Decision Support.

OBJECTIVE: To evaluate determinants of first-pass reperfusion and to develop an explainable machine learning framework for intra-procedural decision s...

Interpretable machine learning reveals the synergistic impact of essential hypertension on early recurrence in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) patients often ential hypertension, yet how systemic vascular stress synergizes with tumor aggressiveness to driv...

Machine learning and plasma growth differentiation factor-15 (GDF15) for early risk stratification of heart failure progression in a long-latency doxorubicin cardiomyopathy model.

BACKGROUND: Anthracycline-induced cardiotoxicity is a major cause of late heart failure (HF) in cancer survivors. Yet early identification of individu...

Serial AI-Enabled Electrocardiogram Trajectories During Heart Failure Treatment: A Proof-of-Concept Case Series.

BACKGROUND: Artificial intelligence-enabled electrocardiogram (AI-ECG) detects left ventricular systolic and diastolic dysfunction at single time poin...