Abstract
Abstract: Automatic recognition of key chest X-ray results to help radiologists with clinical workflow tasks like time-sensitive triage, pneumothorax (CXR) case screening and unanticipated discoveries. Deep learning models have become a promising prediction technique with near human accuracy, but usually suffer from a lack of explain ability. Medical professionals can treat and diagnose illnesses more precisely using automated picture segmentation and feature analysis. In this paper, we propose a model for automatic diagnosis of 14 different diseases based on chest radiographs using machine learning algorithms. Chest X-rays offer a non-invasive (perhaps bedside) method for tracking the course of illness. A severity score prediction model for COVID-19 pneumonia on chest radiography is presented in this study.
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