Automated Pneumonia Diagnosis using a 2D Deep Convolutional Neural Network with Chest X-Ray Images
Kassylkassova K. Omarov B. Kazbekova G. Kozhamkulova Z. Maikotov M. Bidakhmet Z.
2023Science and Information Organization
International Journal of Advanced Computer Science and Applications
2023#14Issue 2699 - 708 pp.
Tiny air sacs in one or both lungs become inflamed as a result of the lung infection known as pneumonia. In order to provide the best possible treatment plan, pneumonia must be accurately and quickly diagnosed at initial stages. Nowadays, a chest X-ray is regarded as the most effective imaging technique for detecting pneumonia. However, performing chest X-ray analysis may be quite difficult and laborious. For this purpose, in this study we propose deep convolutional neural network (CNN) with 24 hidden layers to identify pneumonia using chest X-ray images. In order to get high accuracy of the proposed deep CNN we applied an image processing method as well as rescaling and data augmentation methods as shear_range, rotation, zooming, CLAHE, and vertical_flip. The proposed approach has been evaluated using different evaluation criteria and has demonstrat-ed 97.2%, 97.1%, 97.43%, 96%, 98.8% performance in terms of accuracy, precision, recall, F-score, and AUC-ROC curve. Thus, the applied deep CNN obtain a high level of performance in pneumonia detection. In general, the provided approach is intended to aid radiologists in making an accurate pneumonia diagnosis. Additionally, our suggested models could be helpful in the early detection of other chest-related illnesses such as COVID-19
chest X-rays , CNN , deep learning , Pneumonia , radiology
Text of the article Перейти на текст статьи
L.N.Gumilyov Eurasian National University, Astana, Kazakhstan
Al-Farabi Kazakh National University, Almaty, Kazakhstan
International University of Tourism and Hospitality, Turkistan, Kazakhstan
Khoja Akhmet Yassawi International Kazakh-Turkish University, Turkistan, Kazakhstan
Almaty University of Power Engineering and Telecommunications, Kazakhstan
L.N.Gumilyov Eurasian National University
Al-Farabi Kazakh National University
International University of Tourism and Hospitality
Khoja Akhmet Yassawi International Kazakh-Turkish University
Almaty University of Power Engineering and Telecommunications
10 лет помогаем публиковать статьи Международный издатель
Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026