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Heart Failure

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Enhancing heart failure treatment decisions: interpretable machine learning models for advanced therapy eligibility prediction using EHR data.

BMC medical informatics and decision making
Timely and accurate referral of end-stage heart failure patients for advanced therapies, including heart transplants and mechanical circulatory support, plays an important role in improving patient outcomes and saving costs. However, the decision-mak...

Artificial Intelligence in Heart Failure and Acute Kidney Injury: Emerging Concepts and Controversial Dimensions.

Cardiorenal medicine
BACKGROUND: The growing complexity of patient data and the intricate relationship between heart failure (HF) and acute kidney injury (AKI) underscore the potential benefits of integrating artificial intelligence (AI) and machine learning into healthc...

Characterizing advanced heart failure risk and hemodynamic phenotypes using interpretable machine learning.

American heart journal
BACKGROUND: Although previous risk models exist for advanced heart failure with reduced ejection fraction (HFrEF), few integrate invasive hemodynamics or support missing data. This study developed and validated a heart failure (HF) hemodynamic risk a...

Scalar invariant transform based deep learning framework for detecting heart failures using ECG signals.

Scientific reports
Heart diseases are leading to death across the globe. Exact detection and treatment for heart disease in its early stages could potentially save lives. Electrocardiogram (ECG) is one of the tests that take measures of heartbeat fluctuations. The devi...

Identification of Co-diagnostic Genes for Heart Failure and Hepatocellular Carcinoma Through WGCNA and Machine Learning Algorithms.

Molecular biotechnology
This research delves into the intricate relationship between hepatocellular carcinoma (HCC) and heart failure (HF) by exploring shared genetic characteristics and molecular processes. Employing advanced methodologies such as differential analysis, we...

Incidence, Determinants, and Outcome of Contrast-induced Acute Kidney Injury following Percutaneous Coronary Intervention at a Tertiary Care Hospital.

Saudi journal of kidney diseases and transplantation : an official publication of the Saudi Center for Organ Transplantation, Saudi Arabia
Contrast-induced acute kidney injury (CI-AKI) after percutaneous coronary intervention (PCI) is the common cause of in-hospital acquired AKI and is associated with in-hospital mortality and prolonged hospital stay. We studied the incidence of CI-AKI ...

Heart failure classification using deep learning to extract spatiotemporal features from ECG.

BMC medical informatics and decision making
BACKGROUND: Heart failure is a syndrome with complex clinical manifestations. Due to increasing population aging, heart failure has become a major medical problem worldwide. In this study, we used the MIMIC-III public database to extract the temporal...

Race, Sex, and Age Disparities in the Performance of ECG Deep Learning Models Predicting Heart Failure.

Circulation. Heart failure
BACKGROUND: Deep learning models may combat widening racial disparities in heart failure outcomes through early identification of individuals at high risk. However, demographic biases in the performance of these models have not been well-studied.