title: Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science.
abstract: 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.
authors.affiliation: Computer Science Department, Malaga University, Malaga, Spain.|Malaga Biomedical Research Institute (IBIMA), Malaga, Spain.
authors.forename: Julio
authors.initials: J
authors.lastname: Montes-Torres
authors.affiliation: Computer Science Department, Malaga University, Malaga, Spain.|Yachay Tech University, Urcuqui (Imbabura), Ecuador.|Malaga Biomedical Research Institute (IBIMA), Malaga, Spain.
authors.forename: José Luis
authors.initials: JL
authors.lastname: Subirats
authors.affiliation: Virgen de la Victoria University Hospital, Malaga, Spain.|Malaga Biomedical Research Institute (IBIMA), Malaga, Spain.
authors.forename: Nuria
authors.initials: N
authors.lastname: Ribelles
authors.affiliation: Computer Science Department, Malaga University, Malaga, Spain.|Malaga Biomedical Research Institute (IBIMA), Malaga, Spain.
authors.forename: Daniel
authors.initials: D
authors.lastname: Urda
authors.affiliation: Computer Science Department, Malaga University, Malaga, Spain.|Malaga Biomedical Research Institute (IBIMA), Malaga, Spain.
authors.forename: Leonardo
authors.initials: L
authors.lastname: Franco
authors.affiliation: Virgen de la Victoria University Hospital, Malaga, Spain.|Malaga Biomedical Research Institute (IBIMA), Malaga, Spain.
authors.forename: Emilio
authors.initials: E
authors.lastname: Alba
authors.affiliation: Computer Science Department, Malaga University, Malaga, Spain.|Malaga Biomedical Research Institute (IBIMA), Malaga, Spain.
authors.forename: José Manuel
authors.initials: JM
authors.lastname: Jerez
mesh_terms: D000465:Algorithms; D006801:Humans; D020407:Internet; D008175:Lung Neoplasms / Q000401:mortality*; D000069550:Machine Learning; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D012984:Software; D016019:Survival Analysis