Method and systems for predicting medical conditions and forecasting rate of infection of medical conditions via artificial intellidence models using graph stream processors

A graph stream processing system, comprising:

• an inference module operative to execute instructions on a plurality of graph streaming processors (GSP) to process a digital image associated with a patient, generating an initial prediction utilizing pre-trained weights in a pre-trained deep learning model;
• and
• a post-processing module utilizing the pre-trained deep learning model, the post-processing module operative to execute instructions on the GSP to:
• compute a probability of a medical condition of the patient based on the initial prediction, wherein the computing includes labelling the digital image from the medical condition,
• identify a location of the medical condition in the digital image wherein the identifying comprises generating a plurality of anchor boxes and estimating at least one final anchor that indicates the medical condition, and
• forecast a rate of spread of the medical condition and spread of the medical condition over time based on a plurality of digital images received over time, the initial prediction and additional medical data.