1. Apparatus for predicting occurrence of a medical condition in a patient under consideration comprising: a neural network having weighted connections, an input and an output, said weighted connections resulting from training said neural network; wherein said input is configured to receive data for said patient under consideration and, based on said weighted connections, said neural network is configured to provide at said output a prognostic indicator of the risk of occurrence of the medical condition in said patient; and wherein said neural network is trained with an objective function C for providing a rating of the performance of the neural network, wherein the objective function C is a differentiable approximation of the concordance index, said training of said neural network with the objective function C comprising conducting pair-wise comparisons between prognostic indicators from said neural network of pairs of patients i and j from a training dataset comprising both censored and non-censored data and adapting said weighted connections of said neural network as a result of said comparisons, said pairs of patients from said training dataset comprising: patients i and j who have both experienced the medical condition, and the time t i to occurrence of the medical condition of patient i is shorter than the time t j to occurrence of the medical condition of patient j; and patients i and j where only patient i has experienced the medical condition, and the time t i to occurrence of the medical condition in patient i is shorter than a follow-up visit time t j for patient j.