Bukhori, S.Verdy, B. Y. N.Eka, Y. R. WindiJanuar, A. P.2023-12-142023-12-142023Identification of lung disease types using convolutional neural network and VGG-16 architecture / S. Bukhori, B. Y. N. Verdy, Y. R. Windi Eka, A. P. Januar // Системні дослідження та інформаційні технології : міжнародний науково-технічний журнал. – 2023. – № 3. – С. 96-107. – Бібліогр.: 26 назв.1681–6048https://ela.kpi.ua/handle/123456789/63078Abstract. Pneumonia, tuberculosis, and Covid-19 are different lung diseases but have similar characteristics. One of the reasons for the worsening of disease in lung sufferers is a diagnosis that takes a long time. Another factor, the results of the X-ray photos look blurry and lack contracture, causing different diagnostic results of X-ray photos. This research classifies lung images into four categories: normal lungs, tuberculosis, pneumonia, and Covid-19 using the Convolutional Neural Network method and VGG-16 architecture. The results of the research with models and scenarios without pre-trained use data with a ratio of 9:1 at epoch 50, an accuracy of 94%, while the lowest results are in scenarios using data with a ratio of 8:2 at epoch 50, non-pre-trained models, accuracy by 87%.entuberculosispneumoniaCovid-19VGG-16convolutional neural networkтуберкульозпневмоніязгорткова нейронна мережаArticlePp. 96-107https://doi.org/10.20535/SRIT.2308-8893.2023.3.0762-500000-0002-2527-10800009-0001-7838-0205