What is it about?
Early detection of COVID-19 and pneumonia is crucial for saving lives. This research uses Convolutional Neural Networks (CNN) and hybrid models like CNN+SVM, CNN+RF, and CNN+XGBoost to identify lung diseases from chest X-ray images with high accuracy
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Why is it important?
Pneumonia is described as an acute infection of lung tissue produced by one or more bacteria, and Coronavirus Disease (COVID-19) is a deadly virus that affects the lungs of the human body. The symptoms of COVID-19 disease are closely related to pneumonia. In this work, we identify the patients of pneumonia and coronavirus from chest X-ray images. We used a convolutional neural network for spatial feature learning from X-ray images.
Perspectives
We experimented with pneumonia and coronavirus X-ray images in the Kaggle dataset. Pneumonia and corona patients are classified using a feed-forward neural network and hybrid models (CNN+SVM, CNN+RF, and CNN+Xgboost). The experimental findings on the Pneumonia dataset demonstrate that CNN detects Pneumonia patients with 99.47% recall. The overall experiments on COVID-19 x-ray images show that CNN detected the COVID-19 and pneumonia with 95.45% accuracy.
Richard (Ricky) Smith Jr.
Read the Original
This page is a summary of: A Machine Learning-based Method for COVID-19 and Pneumonia Detection, IgMin Research, July 2024, IgMin Publications Inc.,
DOI: 10.61927/igmin211.
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