Pneumonia Detection Using Chest X Ray Healthcare Through Deep
![pneumonia Detection Using Chest X Ray Healthcare Through Deep pneumonia Detection Using Chest X Ray Healthcare Through Deep](https://ytimg.googleusercontent.com/vi/p8G9IJbmHw0/maxresdefault.jpg)
Pneumonia Detection Using Chest X Ray Healthcare Through Deep There were already enough images in the pneumonia case. therefore, each image of only the normal (healthy) case was augmented twice. finally, after augmentation, there were 3399 healthy chest x ray images and 3623 pneumonia chest x ray images. the settings utilized in image augmentation are shown below in table 2. In this study, we developed a computer aided diagnosis (cad) system that uses an ensemble of deep transfer learning models for the accurate classification of chest x ray images. fig 1. examples of two x ray plates that display (a) a healthy lung and (b) a pneumonic lung.
![pneumonia detection using chest x Ray Cxr Image through deepо pneumonia detection using chest x Ray Cxr Image through deepо](https://www.researchgate.net/publication/339363420/figure/fig4/AS:860631309746185@1582201902346/A-sample-of-CXR-images-having-both-the-classes-separated-into-Train-Validation-and-Test_Q640.jpg)
Pneumonia Detection Using Chest X Ray Cxr Image Through Deepо Abstract. this study investigates the attractive area of ai powered pneumonia detection using chest x rays. recognizing the global significance of pneumonia, it explores various research methodologies to improve the accuracy and speed of diagnosis. the paper highlights the potential of ai in offering precise and timely diagnosis through an. Pneumonia causes the death of around 700,000 children every year and affects 7% of the global population. chest x rays are primarily used for the diagnosis of this disease. however, even for a trained radiologist, it is a challenging task to examine chest x rays. there is a need to improve the diagnosis accuracy. in this work, an efficient model for the detection of pneumonia trained on. Recent advancements in deep learning have shown promising results in various clinical image analysis tasks. among the most commonly performed radiological examinations, chest radiographs play a crucial role and have been extensively investigated for various applications. the availability of large, publicly accessible chest x ray datasets in recent years has sparked research interest. pneumonia. The auroc value of the deep learning algorithm reached 0.923 when detecting pneumonia in chest radiographs with a sensitivity of 95.4%, specificity of 66.0%, ppv of 80.2% and npv of 90.8%. the detection of covid 19 pneumonia in cr by radiologists was achieved with a sensitivity of 50.6% and a specificity of 73%.
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