Publications by authors named "V L D Tomazella"

Human papillomavirus (HPV) infections rank as the most prevalent sexually transmitted infections globally. The Brazilian Ministry of Health recommends the topical use of 70%-90% trichloroacetic acid (TAA) for treating condyloma acuminata, yet this method suffers from a high recurrence rate of 36% and requires roughly six applications. Topical photodynamic therapy (PDT) has shown effectiveness in targeting subclinical lesions, but it also necessitates multiple sessions for complete lesion clearance.

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This article focus on the analysis of the reliability of multiple identical systems that can have multiple failures over time. A repairable system is defined as a system that can be restored to operating state in the event of a failure. This work under minimal repair, it is assumed that the failure has a power law intensity and the Bayesian approach is used to estimate the unknown parameters.

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With advancements in medical treatments for cancer, an increase in the life expectancy of patients undergoing new treatments is expected. Consequently, the field of statistics has evolved to present increasingly flexible models to explain such results better. In this paper, we present a lung cancer dataset with some covariates that exhibit nonproportional hazards (NPHs).

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In this paper, we propose a hierarchical statistical model for a single repairable system subject to several failure modes (competing risks). The paper describes how complex engineered systems may be modelled hierarchically by use of Bayesian methods. It is also assumed that repairs are minimal and each failure mode has a power-law intensity.

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Article Synopsis
  • The paper introduces a new frailty model to analyze survival data considering hidden variations among individuals, using a weighted Lindley distribution for the frailty component.
  • It employs Weibull and Gompertz distributions as baseline hazard functions and utilizes maximum likelihood estimation for inference.
  • The model is tested through simulations and applied to a real-world lung cancer dataset from São Paulo, Brazil, to showcase its effectiveness in detecting unobserved heterogeneity in survival analysis.
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