CGH & IHiS develop AI tool to predict severity of pneumonia in patients

Changi General Hospital (CGH), a 1000-bed academic medical institution under SingHealth located in the eastern part of Singapore, together with the Integrated Health Information System (IHiS), Singapore's national HIT agency, have developed a Community Acquired Pneumonia and COVID-19 Artificial Intelligence (AI) Predictive Engine (CAPE) that can determine the likelihood of whether the patient has mild or severe pneumonia, based on the chest X-ray image. The ability to quickly predict the patient's expected severity of pneumonia would enable clinicians and administrators to efficiently allocate healthcare resources and treat patients, particularly in pandemic situations, where there may be an increased need for inpatient care and critical care support. As pneumonia severity correlates to the degree of Chest X-Ray (CXR) lung image abnormality, CGH's Respiratory and Critical Care Medicine and Radiology teams recognized the potential in leveraging AI to predict the severity of pneumonia from CXR images, and worked with the IHiS Health Insights team to develop CAPE. Using more than 3,000 CXR images and 200,000 data points including lab results and clinical history, CAPE was trained to generate a score for (a) low-risk pneumonia with anticipated short inpatient hospitalization; (b) the risk of mortality (death); and (c) the risk of requiring critical care support – indicators of pneumonia severity – from CXR images. Initial results have been promising – validation tests at CGH showed that CAPE has an approximate accuracy of 80% in predicting the future presence or absence of severe pneumonia.