Background Clinical medicine offers a promising arena for applying Machine Learning (ML)
models. However, despite numerous studies employing ML in medical data analysis, only a …

Aims Heart failure (HF) is one of the most frequent diagnoses for 30-day readmission after
hospital discharge. Nurses have role in reducing unplanned readmission and providing …

Background Heart failure with preserved ejection fraction (HFpEF) is associated with
elevated rates of readmission and mortality. Accurate prediction of readmission risk is …

Cardiovascular disease (CVD) in cancer patients can affect the risk of unplanned
readmissions, which have been reported to be costly and associated with worse mortality …

Background The impact of weather on human health has been proven, but the impact of
extreme weather events on cardiometabolic multimorbidity (CMM) needs to be urgently …

Heart Failure (HF) poses a challenge for our health systems, and early detection of
Worsening HF (WHF), defined as a deterioration in symptoms and clinical and instrumental …

Background Hospital readmissions for heart failure patients remain high despite efforts to
reduce them. Predictive modeling using big data provides opportunities to identify high-risk …

Purpose Observational research provides valuable insights into treatments used in patient
populations in real-world settings. However, confounding is likely to occur if there are …

Background Remote patient management may improve prognosis in heart failure. Daily
review of transmitted data for early recognition of patients at risk requires substantial …

Aims This study aims to develop and validate an optimal model for predicting worsening
heart failure (WHF). Multiple machine learning (ML) algorithms were compared, and the …