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A Bayesian approach for the zero-inflated cure model: an application in a Brazilian invasive cervical cancer database.

Hayala Cristina Cavenague de SouzaFrancisco LouzadaPedro Luiz RamosMauro Ribeiro de Oliveira JúniorGleici de Castro da Silva Perdoná
Published in: Journal of applied statistics (2021)
This paper aims to discuss the Bayesian estimation approach for the zero-inflated cure class of models, which extends the standard cure model by accommodating zero-inflated data in the survival analysis context. A comprehensive simulation study is carried out to assess the performance of the estimation procedure. A new estimation methodology is illustrated using a real dataset related to women diagnosed with invasive cervical cancer in Brazil.
Keyphrases
  • polycystic ovary syndrome
  • electronic health record
  • machine learning
  • emergency department
  • pregnant women
  • skeletal muscle
  • deep learning
  • drug induced