Makine Öğrenmesi Algoritmalarıyla Akciğer Tomografi Görüntülerinden COVID-19 Tespiti

Year 2021, Issue: 28, 630 - 637, 30.11.2021

Özgür Kart , Fatih Basciftci

https://doi.org/10.31590/ejosat.1009611

Cited By: 2

Abstract

Koronavirüs (COVID-19), solunum yolu enfeksiyonuna neden olan ve insandan insana geçebilen bulaşıcı bir virüstür. Bu virüs dünyada kısa sürede etkili olmuş ve bir salgına dönüşmüştür. Bu tür bulaşıcı hastalıkların erken teşhisi ve gerekli tedavinin erken süreçte başlatılması gerekmektedir. COVID-19 hastalığı tespiti için akciğer görüntülerinden ve ağız yoluyla alınan tükrük ile tespit edilmektedir. COVID-19 hastasını RT-PCR (Reverse Transcription- Polymerase Chain Reaction) ile tespit etmek için yaklaşık 4-6 saat sürmektedir. Pandeminin büyüklüğüne bakıldığında çok ta hızlı sayılmamaktadır. Aynı zamanda test kitinin de bir maliyeti bulunmaktadır. Ekonomik olarak güçlü olmayan ülkeler RT-PCR kitlerine erişmekte sorun yaşamaktadır. Pandemi döneminde zorlu süreçlerden bir tanesi her raporu manuel olarak incelemek için, birden fazla radyoloji uzmanı gerekmektedir. Bu çalışmada makine öğrenmesi algoritmaları ile farklı kategorilerdeki akciğer tomografisi görüntülerinden COVID-19 olan görüntü tespit edilmiştir. Orange Data Mining Veri analizi programında makine öğrenmesi algoritması olan K-En Yakın Komşuluk, Yapay Sinir Ağları, Rastgele Orman ve Destek Vektör algoritmaları ile Akciğer veri setinden COVİD-19 hastalığına ait görüntüler sınıflandırılmış, en iyi sonucu Destek Vektör Algoritması ile elde edilmiştir.

Keywords

Yapay Zeka ile hastalık teşhisi, Covid-19 teşhisi, Makine öğrenmesi Algoritmaları, KNN Algoritması, SVM Algoritması, Rastgele Orman Algoritması

COVID-19 Detection from Lung Tomography Images with Machine Learning Algorithms

Abstract

Coronavirus (COVID-19) is a contagious virus that causes respiratory tract infection and can be passed from person to person. This virus became effective in the world in a short time and turned into an epidemic. Early diagnosis of such infectious diseases and the necessary treatment should be initiated in the early period. For the detection of COVID-19 disease, it is detected by lung images and oral saliva. It takes approximately 4-6 hours to detect a COVID-19 patient by RT-PCR (Reverse Transcription- Polymerase Chain Reaction). Considering the size of the pandemic, it is not considered very fast. At the same time, the test kit has a cost. Countries that are not economically strong have problems accessing RT-PCR kits. One of the challenging processes during the pandemic period is to manually review each report, requiring multiple radiologists. In this study, the images with COVID-19 were detected from different categories of lung tomography images with machine learning algorithms. In the Orange Data Mining data analysis program, the images of the COVID-19 disease from the Lung data set were classified with the machine learning algorithm K-Nearest Neighborhood, Artificial Neural Networks, Random Forest and Support Vector algorithms, and the best result was obtained with the Support Vector Algorithm.

Keywords

Disease diagnosis with artificial intelligence, Covid-19 diagnosis, Machine learning Algorithms, KNN Algorithm, SVM Algorithm, Random Forest Algorithm

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