Chest X-ray Analysis Using Deep Learning Algorithm

Abstract

Abstract: Automatic recognition of key chest X-ray results to help radiologists with clinical workflow tasks like time-sensitive triage, pneumothorax (CXR) is crucial Case screening and unanticipated discoveries. Deep learning (DL) 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 thanks to automated picture segmentation and feature analysis. Because diverse equipment provides images with varying image quality, automatic segmentation of medical images is difficult. According to one research,15% of 104 patients with pleural effusion died within 30 days. 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.