AIMC Topic: Heart Failure

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Emerging use of pulmonary artery and cardiac pressure sensing technology in the management of worsening heart failure events.

Heart failure reviews
Unplanned admissions for worsening heart failure (WHF) are the largest resource cost in heart failure (HF) management. Despite advances in pharmacological agents and interventional therapy, HF remains a global epidemic. One crucial-and costly-gap in ...

Optimizing the Primary Prevention of Sudden Cardiac Death in Patients With Heart Failure.

Journal of the American College of Cardiology
Implantable cardioverter-defibrillators (ICDs) protect patients from sudden cardiac death (SCD). Landmark trials demonstrating their efficacy for primary prevention in patients with heart failure (HF) used reduced left ventricular ejection fraction (...

Heart failure monitoring with a single‑lead electrocardiogram at home.

International journal of cardiology
BACKGROUND: Repeated hospitalization due to heart failure (HF) is a significant predictor of mortality. However, there are limited early detection systems for HF progression that can be utilized by patients at home without a cardiac implantable elect...

Predictive Modeling of Heart Failure Outcomes Using ECG Monitoring Indicators and Machine Learning.

Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc
BACKGROUND: Heart failure (HF) is a major driver of global morbidity and mortality. Early identification of patients at risk remains challenging due to complex, multivariate clinical relationships. Machine learning (ML) methods offer promise for more...

Exploring interpretable echo analysis using self-supervised parcels.

Computers in biology and medicine
The application of AI for predicting critical heart failure endpoints using echocardiography is a promising avenue to improve patient care and treatment planning. However, fully supervised training of deep learning models in medical imaging requires ...

Developments in Digital Wearable in Heart Failure and the Rationale for the Design of TRUE-HF (Ted Rogers Understanding of Exacerbations in Heart Failure) Apple CPET Study.

Circulation. Heart failure
BACKGROUND: Heart failure (HF) is a highly prevalent condition characterized by exercise intolerance, an important metric for ambulatory prognostication. However, current methods to assess exercise capacity are often limited to tertiary HF centers, l...

Faster R-CNN approach for estimating global QRS duration in electrocardiograms with a limited quantity of annotated data.

Computers in biology and medicine
In electrocardiography (ECG), measurement of QRS duration (QRSd) is crucial for diagnosing conditions such as left bundle branch block. To address the limited availability of ECG databases with QRS delineation labels, we present a method to use small...

Artificial Intelligence-Enabled Prediction of Heart Failure Risk From Single-Lead Electrocardiograms.

JAMA cardiology
IMPORTANCE: Despite the availability of disease-modifying therapies, scalable strategies for heart failure (HF) risk stratification remain elusive. Portable devices capable of recording single-lead electrocardiograms (ECGs) may enable large-scale com...

Understanding Transient Left Ventricular Ejection Fraction Reduction During Atrial Fibrillation With Artificial Intelligence.

Journal of the American Heart Association
BACKGROUND: Atrial fibrillation (AF) can cause a reduction in left ventricular ejection fraction (LVEF) that resolves rapidly upon restoration of sinus rhythm. We used artificial intelligence to understand (1) how often transient LVEF reduction durin...