AIMC Topic: Natriuretic Peptide, Brain
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Proteomic-based biomarker discovery reveals panels of diagnostic biomarkers for early identification of heart failure subtypes.
Journal of translational medicine
May 15, 2025
BACKGROUND: Limited access to echocardiography can delay the diagnosis of suspected heart failure (HF), which in turn postpones the initiation of optimal guideline-directed medical therapy. Although natriuretic peptides like B-type natriuretic peptid...
Diagnostic MicroRNA Signatures to Support Classification of Pulmonary Hypertension.
Circulation. Genomic and precision medicine
Apr 18, 2025
BACKGROUND: Patients with pulmonary hypertension (PH) are classified based on disease pathogenesis and hemodynamic drivers. Classification informs treatment. The heart failure biomarker NT-proBNP (N-terminal pro-B-type natriuretic peptide) is used to...
Machine learning integration of multimodal data identifies key features of circulating NT-proBNP in people without cardiovascular diseases.
Scientific reports
Apr 8, 2025
N-Terminal Pro-Brain Natriuretic Peptide (NT-proBNP) is important for diagnosing and predicting heart failure or many other diseases. However, few studies have comprehensively assessed the factors correlated with NT-proBNP levels in people with cardi...
Machine learning-based prediction of elevated N terminal pro brain natriuretic peptide among US general population.
ESC heart failure
Nov 19, 2024
AIMS: Natriuretic peptide-based pre-heart failure screening has been proposed in recent guidelines. However, an effective strategy to identify screening targets from the general population, more than half of which are at risk for heart failure or pre...
Machine learning-based model for worsening heart failure risk in Chinese chronic heart failure patients.
ESC heart failure
Sep 7, 2024
AIMS: This study aims to develop and validate an optimal model for predicting worsening heart failure (WHF). Multiple machine learning (ML) algorithms were compared, and the results were interpreted using SHapley Additive exPlanations (SHAP). A clini...
Association of N-terminal pro-B natriuretic peptide with all-cause mortality and cardiovascular mortality in obese and non-obese populations and the development of a machine learning prediction model: National Health and Nutrition Examination Survey (NHANES) 1999-2004.
Diabetes, obesity & metabolism
Sep 6, 2024
AIMS: To explore the potential of N-terminal pro-B natriuretic peptide (NTproBNP) in identifying adverse outcomes, particularly cardiovascular adverse outcomes, in a population with obesity, and to establish a risk prediction model.
A two-stage ensemble learning based prediction and grading model for PD-1/PD-L1 inhibitor-related cardiac adverse events: A multicenter retrospective study.
Computer methods and programs in biomedicine
Aug 5, 2024
BACKGROUND: Immune-related cardiac adverse events (ircAEs) caused by programmed cell death protein-1 (PD-1) and programmed death-ligand-1 (PD-L1) inhibitors can lead to fulminant and even fatal consequences. This study aims to develop a prediction an...
Multimodal deep learning models utilizing chest X-ray and electronic health record data for predictive screening of acute heart failure in emergency department.
Computer methods and programs in biomedicine
Jul 29, 2024
BACKGROUND AND OBJECTIVES: Ambiguity in diagnosing acute heart failure (AHF) leads to inappropriate treatment and potential side effects of rescue medications. To address this issue, this study aimed to use multimodality deep learning models combinin...
AI-enabled cardiac chambers volumetry in coronary artery calcium scans (AI-CAC) predicts heart failure and outperforms NT-proBNP: The multi-ethnic study of Atherosclerosis.
Journal of cardiovascular computed tomography
Apr 24, 2024
INTRODUCTION: Coronary artery calcium (CAC) scans contain useful information beyond the Agatston CAC score that is not currently reported. We recently reported that artificial intelligence (AI)-enabled cardiac chambers volumetry in CAC scans (AI-CAC™...
Computed Tomography Angiography
Heart Failure
Natriuretic Peptide, Brain
Multidetector Computed Tomography
Reproducibility of Results
Middle Aged
Humans
Vascular Calcification
Risk Factors
Predictive Value of Tests
Risk Assessment
Artificial Intelligence
Asymptomatic Diseases
Aged
Incidence
Coronary Angiography
Biomarkers
Aged, 80 and over
Time Factors
Peptide Fragments
Prognosis
Male
United States
Radiographic Image Interpretation, Computer-Assisted
Female
Coronary Artery Disease
Prediction of adverse cardiovascular events in children using artificial intelligence-based electrocardiogram.
International journal of cardiology
Apr 3, 2024
BACKGROUND: Convolutional neural networks (CNNs) have emerged as a novel method for evaluating heart failure (HF) in adult electrocardiograms (ECGs). However, such CNNs are not applicable to pediatric HF, where abnormal anatomy of congenital heart de...
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