https://www.selleckchem.com/products/gsk621.html
934 (38%) patients died or were discharged to hospice. The model achieved an AUC of 0.88 (95% CI, 0.84-0.92) with only the initial 24h EHR data, and 0.94 (95% CI, 0.92-0.96) after the next 24h. EHR data and machine learning models can accurately predict the risk of the adverse outcome for critically ill nontraumatic SAH patients. It is possible to use EHR data and machine learning techniques to help with clinical decision-making. EHR data and machine learning models can accurately predict the risk of the adverse outcome for critically il
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