Early prediction of mortality of septic patients visiting emergency room using machine learning
J. Heo (Chuncheon-si, Republic of Korea), Y. Heo (Chuncheon-si, Republic of Korea), D. Moon (Chuncheon-si, Republic of Korea), S. Bak (Chuncheon-si, Republic of Korea), W. Kim (Chuncheon-si, Republic of Korea), S. Han (Chuncheon-si, Republic of Korea), S. Choi (Chuncheon-si, Republic of Korea), D. Kim (Chuncheon-si, Republic of Korea), Y. Kim (Chuncheon-si, Republic of Korea), H. Choi (Chuncheon-si, Republic of Korea)
Source: International Congress 2022 – COVID-19 acute respiratory distress syndrome and beyond
   
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J. Heo (Chuncheon-si, Republic of Korea), Y. Heo (Chuncheon-si, Republic of Korea), D. Moon (Chuncheon-si, Republic of Korea), S. Bak (Chuncheon-si, Republic of Korea), W. Kim (Chuncheon-si, Republic of Korea), S. Han (Chuncheon-si, Republic of Korea), S. Choi (Chuncheon-si, Republic of Korea), D. Kim (Chuncheon-si, Republic of Korea), Y. Kim (Chuncheon-si, Republic of Korea), H. Choi (Chuncheon-si, Republic of Korea). Early prediction of mortality of septic patients visiting emergency room using machine learning. 2316
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