A form of pneumonia, presenting as opacities with in a patient’s lungs, is the most common presentation associated with the COVID-19 virus, and great attention has gone into how these changes relate to patient morbidity and mortality. Recent research suggests that the percentage of Well-Aerated-Lung correlates to clinical outcomes, such as the need for ventilator support, ICU admission and death in case of COVID-19 patients. L3-Net is an open source segmentation and classification model for analyzing COVID-19 infections in chest CT-Scans. The percentage of lung involvement is a valuable metric that is difficult to accurately measure without advanced software tools. Utilizing a machine to accurately calculate the lung involvement ratio and absolute volume will be a valuable metric for researchers to use to prognosticate patients with COVID-19 and other respiratory illnesses.
Input variables : Chest CT scans of COVID-19 patients
Output Variables : Segmentation of a COVID-19 patient in one of the following categories: Pure Ground Glass Opacification, GGO w/ Smooth Interlobular Septal Thickening, GGO w/ Intralobular Lines (Crazy Paving), Organizing Pneumonia Pattern, GGO w/ Peripheral Consolidation, Consolidation
| Statistical | : | Somers D | Accuracy | Precision and Recall | Confusion Matrix | F1 Score | Roc and Auc | Prevalence | Detection Rate | Balanced Accuracy | Cohen's Kappa | Concordance | Gini Coefficent | KS Statistic | Youden's J Index |
| Business | : | Population at High Risk of Disease | Risk by Geography | Risk by Demographics | Risk by Clinical Parameters | Optimized Hospital Resource Utilization | Decreased Cost of Care | Decreased Patient Visits |
| Infrastructure | : | Log Bytes | Logging/User/IAMPolicy | Logging/User/VPN | CPU Utilization | Memory Usage | Error Count | Prediction Count | Prediction Latencies | Private Endpoint Prediction Latencies | Private Endpoint Response Count |
Visit Model : github.com
Additional links : arxiv.org
| Model Category | : | Public |
| Date Published | : | July, 2020 |
| Healthcare Domain | : | Provider |
| Code | : | github.com |
| Medical Imaging |
| Health Risk Prediction |