Cox model and decision trees: an application to breast cancer data.

Objective: To evaluate, using semiparametric methodologies of survival analysis, the relationship between covariates and time to death of patients with breast cancer, as well as the determination discriminatory power in the conditional inference tree of patients who had cancer.

Methods: A retrospective cohort study was conducted using data collected from medical records of women who had breast cancer and underwent treatment between 2005 and 2015 at the Hospital da Fundação de Assistencial da Paraíba in Campina Grande, State of Paraiba, Brazil. Survival curves were estimated using the Kaplan-Meier method, Cox regression, and conditional decision tree.

Extracting Rules via Markov Chains for Cryptocurrencies Returns Forecasting.

With the growing popularity of digital currencies known as cryptocurrencies, there is a need to develop models capable of robustly analyzing and predicting the value of future returns in these markets. In this article, we extract behavior rules to predict the values of future returns in the Bitcoin, Ethereum, Litecoin, and Ripple closing series. We used categorical data in the analyses and Markov chain models from the first to the tenth order to propose a new way of establishing possible future scenarios, in which we analyze the dependence of memory on the dynamics of the process.