In November of 2018, 16 Bit placed 4th in the RSNA ML challenge for pneumonia detection. The challenge included 1,400 teams, with 346 submitting results. Using a publicly available chest x-ray dataset from the NIH that was annotated for probable pneumonia, the teams trained and tested their models with a goal of improving patient care. Luciano Prevedello, M.D., M.P.H., chair of the Machine Learning Steering Subcommittee of the RSNA Radiology Informatics Committee stated that by organizing ML challenges, RSNA is playing an important role in fostering and demonstrating the capability of AI to provide valuable tools for radiology. By participating in these challenges, 16 Bit is demonstrating our capabilities to design these tools.
