Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Predicting the risk of mortality and rehospitalization in heart failure patients: A retrospective cohort study by machine learning approach
12
Zitationen
8
Autoren
2024
Jahr
Abstract
The ML-based risk stratification tool was able to assess the risk of 5-year all-cause mortality and readmission in patients with HF. ML could provide an explicit explanation of individualized risk prediction and give physicians an intuitive understanding of the influence of critical features in the model.
Ähnliche Arbeiten
Corrigendum to: 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: Developed by the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) With the special contribution of the Heart Failure Association (HFA) of the ESC.
2021 · 19.535 Zit.
2013 ACCF/AHA Guideline for the Management of Heart Failure
2013 · 12.581 Zit.
2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure
2021 · 12.105 Zit.
Should We STOP Angiotensin Converting Enzyme Inhibitors/Angiotensin Receptor Blockers in Advanced Kidney Disease?
2016 · 11.730 Zit.
K/DOQI clinical practice guidelines for chronic kidney disease: Evaluation, classification, and stratification
2002 · 11.655 Zit.