Researchers have trained machine learning models using a large dataset to identify five subtypes of heart failure, which may improve risk prediction and treatment.

Researchers found that, depending on the patients' other clinical information, adding the SDI into the risk-prediction model could even double the probability of that patient developing heart ...

A study was conducted to determine the performance of a novel congestion index to predict heart failure events compared with standard weight-based rules.

In this case report, restrictive cardiomyopathy and congestive heart failure associated with left atrial and sinus venosus dilation were diagnosed in a 2-yr-old captive lethargic McDowell's carpet ...