14. A method for knowledge-based interpretable predictive modeling of patients, the method comprising: training, with machine training using training data for a plurality of previous lung cancer patients, a graphic model to predict survivability of lung cancer based on relationships between variables from a lung cancer expert, the training data including previous patient values for the variables, the variables including the survivability; applying, with a processor, current patient values of the variables for a current lung cancer patient to the graphic model, the graphic model configured to predict even with one of the variables not having a current patient value as a function of the relationships; displaying a representation of the graphic model, the representation showing the variables and the relationships remaining after training; and displaying the survivability for the current lung cancer patient predicted by the graphic model, wherein the variables comprise tumor load, T-stage, N-stage, number of lymph node stations, WHO performance, and the survivability.
14. A method for knowledge-based interpretable predictive modeling of patients, the method comprising: training, with machine training using training data for a plurality of previous lung cancer patients, a graphic model to predict survivability of lung cancer based on relationships between variables from a lung cancer expert, the training data including previous patient values for the variables, the variables including the survivability; applying, with a processor, current patient values of the variables for a current lung cancer patient to the graphic model, the graphic model configured to predict even with one of the variables not having a current patient value as a function of the relationships; displaying a representation of the graphic model, the representation showing the variables and the relationships remaining after training; and displaying the survivability for the current lung cancer patient predicted by the graphic model, wherein the variables comprise tumor load, T-stage, N-stage, number of lymph node stations, WHO performance, and the survivability. 19. The method of claim 14 further comprising outputting confidence information with the survivability.