​A locally developed AI tool can accurately predict the severity of pneumonia from CXR images with an approximate accuracy of 80%. Jointly developed by CGH and IHiS, CAPE was trained to generate a score for (a) low-risk pneumonia with anticipated short inpatient hospitalisation; (b) the risk of mortality (death); and (c) the risk of requiring critical care support. Dr Charlene Liew, Project Lead and Deputy Chief Medical Informatics Officer, CGH said one main advantage is that the risk of patients requiring critical care can be calculated almost instantaneously. Emergency Department and ward doctors can receive an early warning for possible clinical deterioration and prescribe the appropriate interim measures to improve patient outcomes.