Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Trustworthiness of a machine learning early warning model in medical and surgical inpatients
3
Zitationen
8
Autoren
2024
Jahr
Abstract
Characterization of the target patient subpopulations has clinical implications and should be considered when developing models to be used in general hospital wards.
Ähnliche Arbeiten
Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study
2020 · 28.965 Zit.
The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3)
2016 · 26.835 Zit.
APACHE II
1985 · 13.504 Zit.
Definitions for Sepsis and Organ Failure and Guidelines for the Use of Innovative Therapies in Sepsis
1992 · 13.152 Zit.
The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure
1996 · 11.408 Zit.