Background Heart failure (HF), a global health challenge, requires innovative diagnostic and
management approaches. The rapid evolution of deep learning (DL) in healthcare …

Accurate prediction of heart failure can help prevent life-threatening situations. Several
factors contribute to the risk of heart failure, including underlying heart diseases such as …

Heart failure is an incurable disease and shows general symptoms. The presence of general
symptoms contrary to specific indications makes early diagnosis difficult. This study aims to …

Results: Upon evaluation using different metrics, the performance of the machine learning
models varied. Logistic regression demonstrated the highest accuracy in predicting heart …

this paper examines the usage of a bi-directional lengthy brief period memory (LSTM)
network to assess the hazard of cardiac arrest in a populace of elderly individuals. Firstly …

Chronic diseases are one of the leading causes of death worldwide, with diabetes,
hypertension, congestive heart failure, and chronic obstructive pulmonary disease among …

Predicting survival in patients with heart disease clinically is a challenging task. Predicting
the survival state is very important among patients with heart failure. In this paper, we …

Background: There has been a rapid growth in the application of structured Electronic
Health Records (EHRs) to healthcare systems, where huge amounts of diagnosis codes …