Missing data is a common occurrence in clinical research. Missing data occurs when the
value of the variables of interest are not measured or recorded for all subjects in the sample …

Background Patients with acute heart failure are frequently or systematically hospitalized,
often because the risk of adverse events is uncertain and the options for rapid follow-up are …

Background Machine learning (ML) methods are increasingly used in addition to
conventional statistical modelling (CSM) for predicting readmission and mortality in patients …

Aims This study aimed to review the performance of machine learning (ML) methods
compared with conventional statistical models (CSMs) for predicting readmission and …

During myocardial infarction, microcirculation disturbance in the ischemic area can cause
necrosis and formation of fibrotic tissue, potentially leading to malignant arrhythmia and …

The Cox proportional hazards model is used extensively in clinical and epidemiological
research. A key assumption of this model is that of proportional hazards. A variable satisfies …

Background Although echocardiography is widely used to measure left ventricular ejection
fraction (LVEF), its prognostic value has not been demonstrated in a broad range of patients …

Hospital at home (HaH) is an innovative care model that may be particularly suited for heart
failure (HF). Outpatient visits and inpatient care have been the 2 traditional settings for HF …

Study objective We use variables from a recently derived acute heart failure risk-stratification
rule (STRATIFY) as a basis to develop and optimize risk prediction using additional patient …

Aim We studied the association between neighbourhood material deprivation, a metric
estimating inability to attain basic material needs, with outcomes and processes of care …