During the coronavirus disease 2019 (COVID-19) pandemic, accurate and timely triage of patients at the emergency department is critical for informing decision-making. The model is an AI system that can predict deterioration in COVID-19 patients who present to the emergency department, with deterioration defined as the composite outcome of mortality, intubation, or ICU admission. Model is using a deep neural network that learns from chest X-ray images and a gradient boosting model that learns from routine clinical variables like vital signs, laboratory tests. The model's goal is to provide clinicians with a quantitative estimate of the risk of deterioration and how it is expected to evolve over time, allowing for efficient triage and prioritisation of patients. at the high risk of deterioration.
Input variables : Chest X-ray images, routine clinical variables,
Output Variables : Predicted deterioration of COVID-19 patients
Visit Model : github.com
Additional links : arxiv.org
| Model Category | : | Public |
| Date Published | : | August, 2020 |
| Healthcare Domain | : | Provider |
| Code | : | github.com |
| Utilization Management |
| ED Admission |