One of the prevailing applications of machine learning is the use of predictive modelling in
clinical survival analysis. In this work, we present our view of the current situation of computer tools for survival analysis, stressing the need of transferring the latest results in the
field of machine learning to biomedical researchers. We propose a web based software for
survival analysis called OSA (Online Survival Analysis), which has been developed as an
open access and user friendly option to obtain discrete time, predictive survival models at
individual level using machine learning techniques, and to perform standard survival analysis. OSA employs an Artificial Neural Network (ANN) based method to produce the predictive survival models. Additionally, the software can easily generate survival and hazard
curves with multiple options to personalise the plots, obtain contingency tables from the
uploaded data to perform different tests, and fit a Cox regression model from a number of
predictor variables. In the Materials and Methods section, we depict the general architecture
of the application and introduce the mathematical background of each of the implemented
methods. The study concludes with examples of use showing the results obtained with public datasets.
