A shiny app for modeling the lifetime in primary breast cancer patients through phase-type distributions
Metadata
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AIMS Press
Materia
Phase-type distributions Modelling Lifetime
Date
2023-12-29Referencia bibliográfica
Christian Acal, Elena Contreras, Ismael Montero, Juan Eloy Ruiz-Castro. A shiny app for modeling the lifetime in primary breast cancer patients through phase-type distributions[J]. Mathematical Biosciences and Engineering, 2024, 21(1): 1508-1526. doi: 10.3934/mbe.2024065
Sponsorship
Project PID2020-113961GB-I00 funded by MCIN/ AEI /10.13039/501100011033 of the Spanish Ministry of Science and Innovation (also supported by the FEDER programme); "María de Maeztu" Excellence Unit IMAG reference CEX2020-001105-M, funded by MCIN/AEI/10.13039/501100011033/; Project FQM-307 of the Government of Andalusia (Spain)Abstract
Phase-type distributions (PHDs), which are defined as the distribution of the lifetime up to the absorption in an absorbent Markov chain, are an appropriate candidate to model the lifetime of any system, since any non-negative probability distribution can be approximated by a PHD with sufficient precision. Despite PHD potential, friendly statistical programs do not have a module implemented in their interfaces to handle PHD. Thus, researchers must consider others statistical software such as R, Matlab or Python that work with the compilation of code chunks and functions. This fact might be an important handicap for those researchers who do not have sufficient knowledge in programming environments. In this paper, a new interactive web application developed with shiny is introduced in order to adjust PHD to an experimental dataset. This open access app does not require any kind of knowledge about programming or major mathematical concepts. Users can easily compare the graphic fit of several PHDs while estimating their parameters and assess the goodness of fit with just several clicks. All these functionalities are exhibited by means of a numerical simulation and modeling the time to live since the diagnostic in primary breast cancer patients.