AIMC Topic: Heart Failure

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Proteomic-based biomarker discovery reveals panels of diagnostic biomarkers for early identification of heart failure subtypes.

Journal of translational medicine
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...

Unveiling mitochondrial-targeting compounds in Qishenyiqi dropping pills for heart failure treatment: An integrative UHPLC-QTOF MS and high-content imaging strategy.

Journal of pharmaceutical and biomedical analysis
Mitochondrial dysfunction, a central pathogenic driver of heart failure (HF), underscores the therapeutic imperative to preserve mitochondrial homeostasis. Qishenyiqi dropping pills (QSYQ), a clinically validated traditional Chinese formulation, exhi...

SEISMIC-HF 1: key findings from AHA24 and implications for remote cardiac monitoring.

Heart failure reviews
While there is continued progress in developing therapies for patients with heart failure, the condition results in significant morbidity and a sizeable economic impact on our society. Recent advances in wearable sensors combined with machine learnin...

Elucidating predictors of preoperative acute heart failure in older people with hip fractures through machine learning and SHAP analysis: a retrospective cohort study.

BMC geriatrics
BACKGROUND: Acute heart failure (AHF) has become a significant challenge in older people with hip fractures. Timely identification and assessment of preoperative AHF have become key factors in reducing surgical risks and improving outcomes.

Development of an Artificial Intelligence-Enabled Electrocardiography to Detect 23 Cardiac Arrhythmias and Predict Cardiovascular Outcomes.

Journal of medical systems
Arrhythmias are common and can affect individuals with or without structural heart disease. Deep learning models (DLMs) have shown the ability to recognize arrhythmias using 12-lead electrocardiograms (ECGs). However, the limited types of arrhythmias...

Construction of a deep learning model and identification of the pivotal characteristics of FGF7- and MGST1- positive fibroblasts in heart failure post-myocardial infarction.

International journal of biological macromolecules
Dysregulation of fibroblast function is closely associated with the occurrence of heart failure after myocardial infarction (post-MI HF). Myocardial fibrosis is a detrimental consequence of aberrant fibroblast activation and extracellular matrix depo...

AI analysis for ejection fraction estimation from 12-lead ECG.

Scientific reports
Heart failure (HF) remains a leading global cause of cardiovascular deaths, with its prevalence expected to rise in the upcoming decade. Measuring the heart ejection fraction (EF) is crucial for diagnosing and monitoring HF. Although echocardiography...

Identification of hub genes for the diagnosis associated with heart failure using multiple cell death patterns.

ESC heart failure
AIMS: Heart failure (HF) is an important public health problem worldwide, and programmed cell death (PCD) plays a crucial role in its pathologic process. This study aims to identify the hub genes associated with HF through PCD in order to better unde...

Artificial Intelligence in Diagnosis of Heart Failure.

Journal of the American Heart Association
Heart failure (HF) is a complex and varied condition that affects over 50 million people worldwide. Although there have been significant strides in understanding the underlying mechanisms of HF, several challenges persist, particularly in the accurat...