Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Machine Learning Model for Predicting Mortality Risk in Patients With Complex Chronic Conditions: Retrospective Analysis
4
Zitationen
8
Autoren
2023
Jahr
Abstract
This study showcases encouraging outcomes in forecasting mortality among patients with intricate and persistent health conditions. The employed variables are conveniently accessible, and the incorporation of health care resource utilization information of the patient, which has not been employed by current state-of-the-art approaches, displays promising predictive power. The proposed prediction model is designed to efficiently identify cases that need customized care and proactively anticipate the demand for critical resources by health care providers.
Ähnliche Arbeiten
A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation
1987 · 49.462 Zit.
Frailty in Older Adults: Evidence for a Phenotype
2001 · 24.121 Zit.
Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017
2018 · 13.894 Zit.
Coding Algorithms for Defining Comorbidities in ICD-9-CM and ICD-10 Administrative Data
2005 · 10.522 Zit.
Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases
1992 · 10.501 Zit.