SYSTEM AND METHOD FOR PREDICTING SEQUENTIAL ORGAN FAILURE ASSESSMENT (SOFA) SCORES USING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING

摘要

Various aspects of the subject technology related to systems and methods for predicting sequential organ failure assessment (SOFA) scores using machine learning. A system may be configured to receive patient data including one or more features associated with one or more patients. The system may process the features using one or more SOFA score prediction models derived from at least one machine learning process to output respective predicted SOFA scores. One of the prediction models has been trained to output a first SOFA component score for a first amount of time into the future and a second prediction model has been trained to output a second SOFA component score for the first amount of time into the future. The system may output on a graphical user interface, a total SOFA score, the first SOFA component score, and the second SOFA components score predicted for the respective patient.