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Journals / Politeknik Dergisi / 2025 / Cilt: 28 Sayı: 6

Use of Chest X-ray Images and Artificial Intelligence Methods for Early Diagnosis of COVID-19

COVID-19’un Erken Teşhisi için Göğüs Röntgeni Görüntülerinin ve Yapay Zeka Yöntemlerinin Kullanımı

Maral A. Mustafa(GAZİ ÜNİVERSİTESİ)0000-0002-0601-3457
O. Ayhan Erdem(GAZİ ÜNİVERSİTESİ)0000-0001-7761-1078
Esra Söğüt(Gazi Üniversitesi)0000-0002-0051-2271
Pages
1717–1729
Publication Date
2025-12-04
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The result of this investigation could be used to design an effective and reliable tool for COVID-19 diagnosis and evaluation.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The worldwide epidemic brought on by COVID-19 has substantially hurt people’s health.
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Key Findings & Data:To discover and treat ill people, given the significant usage of efficient screening and diagnostic methods, as well as a crucial way to this deadly illness.
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Conclusion & Impact:The result of this investigation could be used to design an effective and reliable tool for COVID-19 diagnosis and evaluation.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Covid-19 sınıflandırılması · VGG16 · resnet

Abstract

The worldwide epidemic brought on by COVID-19 has substantially hurt people’s health. To discover and treat ill people, given the significant usage of efficient screening and diagnostic methods, as well as a crucial way to this deadly illness. One strategy that might be used to help with COVID-19 early diagnosis is to make use of X-ray pictures of individuals’ chests. Different Computer Aided Diagnosis (CAD) methods have been created to aid doctors in doing this work by providing them more extra information and suggestions. This investigation uses pictures of chest X-rays taken to create a CAD method for COVID-19 illness. Convolutional Neural Network (CNN), Resnet50, Xception, Densnet, Mobilenet, VGG16, Resnet152v2, and Inceptionv3 will use in the investigation to examine the pictures and remark on automatic detection and categorization of COVID-19 cases. The effectiveness of each method will be examined on a big collection of chest X-ray pictures to identify its accuracy and reliability in detecting COVID-19 cases. The result of this investigation could be used to design an effective and reliable tool for COVID-19 diagnosis and evaluation.

Özet

COVID-19'un yol açtığı küresel salgın, insan sağlığı üzerinde önemli olumsuz etkilere neden olmuştur. Bu ölümcül hastalığın tespiti ve tedavisi için etkili tarama ve tanı yöntemlerinin yaygın kullanımı büyük önem taşımaktadır. COVID-19'un erken teşhisine yardımcı olabilecek stratejilerden biri, hastaların göğüs röntgeni (X-ray) görüntülerinden faydalanmaktır. Doktorlara ek bilgi ve öneriler sağlayacak ve hastalık teşhis sürecini destekleyecek çeşitli Bilgisayar Destekli Tanı (BDT) yöntemleri geliştirilmekte ve kullanılmaktadır. Bu çalışma COVID-19 hastalığının teşhisini gerçekleştirmek üzere göğüs röntgeni görüntülerini temel alan bir BDT yöntemi geliştirmeyi amaçlamaktadır. Görsellerin analiz edilmesi ve COVID-19 vakalarının otomatik tespitine ve sınıflandırılmasına yönelik değerlendirme yapılabilmesi için Evrimsel Sinir Ağları (ESA), ResNet50, Xception, DenseNet, MobileNet, VGG16, ResNet152v2 ve Inceptionv3 gibi modeller kullanılmaktadır. Her yöntemin etkinliği geniş ölçekli bir göğüs röntgeni veri kümesi üzerinde test edilmekte ve COVID-19 vakalarının tespitindeki doğruluk ve güvenilirlik durumları değerlendirilmektedir. Bu çalışmadan elde edilen sonuçlar, COVID-19'un teşhis ve değerlendirilmesine yönelik etkili ve güvenilir bir tanı aracı geliştirilmesi için temel oluşturacaktır.

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Cite This Article

Mustafa, M. A., Erdem, O. A., Söğüt, E. (2025). Use of Chest X-ray Images and Artificial Intelligence Methods for Early Diagnosis of COVID-19. Politeknik Dergisi, Cilt: 28 Sayı: 6, 1717–1729. https://doi.org/10.2339/politeknik.1654887

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