We propose a cluster-weighted model to analyze the mortality and the latent heterogeneity of COVID-19 patients. We focus on administrative data col- lected during in the earliest phases of the COVID-19 pandemic. Results highlight that a model-based clustering approach is helpful to detect unobserved clusters of COVID-19 patients.

A cluster-weighted model for COVID- 19 hospital admissions

Salvatore Ingrassia
Methodology
;
Giorgio Vittadini
Methodology
2024-01-01

Abstract

We propose a cluster-weighted model to analyze the mortality and the latent heterogeneity of COVID-19 patients. We focus on administrative data col- lected during in the earliest phases of the COVID-19 pandemic. Results highlight that a model-based clustering approach is helpful to detect unobserved clusters of COVID-19 patients.
2024
978-88-5509-645-4
Cluster-Weighted Models
COVID-19, clustering
administrative data
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/618409
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact