![]() A neural network model that was pre-trained on large (non-COVID-19) chest X-ray datasets is used to construct features for COVID-19 images which are predictive for our task. Images from a public COVID-19 database were scored retrospectively by three blinded experts in terms of the extent of lung involvement as well as the degree of opacity. ![]() Such a tool can gauge the severity of COVID-19 lung infections (and pneumonia in general) that can be used for escalation or de-escalation of care as well as monitoring treatment efficacy, especially in the ICU. ![]() In this study, we present a severity score prediction model for COVID-19 pneumonia for frontal chest X-ray images. Chest X-rays (CXRs) provide a non-invasive (potentially bedside) tool to monitor the progression of the disease. The need to streamline patient management for coronavirus disease-19 (COVID-19) has become more pressing than ever.
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