Juliana Cobre

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A common interest in gene expression data analysis is to identify from a large pool of candidate genes the genes that present significant changes in expression levels between a treatment and a control biological condition. Usually, it is done using a statistic value and a cutoff value that are used to separate the genes differentially and nondifferentially(More)
Existing cure-rate survival models are generally not convenient for modeling and estimating the survival quantiles of a patient with specified covariate values. This paper proposes a novel class of cure-rate model, the transform-both-sides cure-rate model (TBSCRM), that can be used to make inferences about both the cure-rate and the survival quantiles. We(More)
In this paper, we proposed a mechanistic breast cancer survival model based on the axillary lymph node chain structure, considering lymph nodes as a potential dissemination arrangement. We assume a naive breast cancer treatment protocol consisting of exposing patients first to a chemotherapy treatment on r intervals at k-cycles separated by equal time(More)
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