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Using Machine Learning to Estimate Mortality Risk After Heart Failure (IMAGE)

Juntendo University researchers have trained a machine learning algorithm to use clinical information and physical function ...
BMJ

Machine learning methods, applications and economic analysis to predict heart failure hospitalisation risk: a scoping review

Background Machine Learning (ML) has been transformative in healthcare, enabling more precise diagnostics, personalised treatment regimens and enhanced patient care. In cardiology, ML plays a crucial ...
IEEE

Early Prediction of Heart Diseases Using Machine Learning Algorithms-A Review

Abstract: Predicting the onset of cardiovascular disease at an early stage using machine learning algorithms is the primary goal of this research. Improved model performance, reduced overfitting, ...
IEEE

Detection of Valvular Heart Diseases From PCG Signals Using Machine and Deep Learning Models: A Review

Abstract: Artificial intelligence (AI) predictions are widely used to address challenges in the heart health sector, such as providing clinical decision support. Early detection of valvular heart ...
Frontiers

Machine learning prediction of ARDS after heart valve surgery: development and validation in Northwest China

Objective: To develop an AI-based predictive model for acute respiratory distress syndrome (ARDS) following cardiopulmonary bypass (CPB)-assisted heart valve replacement (HVR) to enable early ...