Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Machine learning risk prediction models for medication harm in hospitalised adult patients
0
Zitationen
6
Autoren
2026
Jahr
Abstract
This study highlights the potential of ML models to predict medication harm, enabling early identification of high-risk patients for preventive interventions. Interdisciplinary collaboration is essential in developing robust, clinically relevant models that can be used to improve patient safety.
Ähnliche Arbeiten
To Err Is Human
2000 · 14.080 Zit.
A Surgical Safety Checklist to Reduce Morbidity and Mortality in a Global Population
2009 · 5.552 Zit.
Incidence of Adverse Events and Negligence in Hospitalized Patients
1991 · 4.650 Zit.
An Intervention to Decrease Catheter-Related Bloodstream Infections in the ICU
2006 · 4.347 Zit.
The Nature of Adverse Events in Hospitalized Patients
1991 · 3.736 Zit.