Looking to gauge flu season’s severity? Ask CMU computer scientists, statisticians

Updated 7 hours ago A man-vs.-machine competition is shaping up among faculty and students at Car‑negie Mellon University trying to forecast the spread of the flu. The U.S. Centers for Disease Control and Prevention announced Friday that CMU’s DELPHI research group developed the top three forecasting models for the flu last year, beating out 11 others. CMU’s top forecasting model was a computer that used artificial intelligence and machine learning to make predictions based on past patterns from the CDC data, said Roni Rosenfeld, professor in the School of Computer Science’s Machine Learning Department and Language Technologies Institute and a DELPHI group member. In second place was a forecasting model that relied on crowd-sourced predictions that people made based on news reports, personal experience, expertise and other factors. That model…


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