Publication number: 20230051833
Abstract: Systems and methods of epidemiological modeling using machine learning are provided, and can include receiving values for an occurrence of the infectious disease during a first time period, generating, from a model trained by a machine learning system, predictions for the occurrence of the infectious disease over a second time period, performing, by a simulator using the predictions, one or more simulations of the occurrence of the infectious disease in one or more geographic regions during one or more time periods subsequent to the second time period, and providing, to a user interface, a first simulation of the one or more simulations performed by the simulator for a first geographic region of the one or more geographic regions during a time period of the one or more time periods.
July 28, 2022
February 16, 2023
Jeremy Achin, Michael Schmidt, Mackenzie Heiser, Jona Sassenhagen, Oleg Baranovskiy, Jared Shamwell, Hon Nian Chua, Joao Paulo Gomes, Maxence Jeunesse, Yung Siang Liau, Julian Wergieluk, Jay Cameron Schuren, Mark Steadman, Mohak Saxena, Samuel Clark, Noa Flaherty, Jarred Bultema, Nathan Robert Cameron, Amanda Schierz, Vinay Venkata Wunnava, Xavier Conort, Gregory Michaelson, Anton Suslov, Madeleine Mott, Sergey Yurgenson, Christopher James Monsour, Matthew Joseph Nitzken, Patrick Allen Farrell, Jared Bowns, Dustin Burke, Ievgenii Baliuk, Rishabh Raman