The invention discloses a disease prognosis prediction system based on deep semi-supervised multi-task learning survival analysis. The disease prognosis prediction system comprises a data acquisitionmodule, a data preprocessing module, a prediction model construction module and the like. On the basis of a deep neural network model, a survival analysis problem is converted into a multi-task learning model composed of a semi-supervised learning problem of multi-time-sequence-point survival probability prediction; the model directly models the survival probability, does not depend on proportional risk hypothesis, can fit a time-dependent effect, and has better interpretability; a semi-supervised loss function and a sorting loss function are utilized to fit the data, complete data and deleteddata are fully utilized, and a traditional survival analysis problem and a survival analysis problem considering competition risks can be solved; according to the model, through multi-task learning of multiple time sequence points, data sharing among multiple prediction tasks is achieved, mutual constraint among the multiple prediction tasks is achieved, and the generalization ability of the model is improved.