Academic Journal
DERİN SİNİR AĞLARI VE YENİDEN ÖRNEKLEME METOTLARI İLE RUTİN KAN TESTLERİNE DAYALI COVID-19 TESPİTİ ; Covid-19 Detection Based on Routine Blood Tests With Deep Neural Networks and Resampling Methods
| العنوان: | DERİN SİNİR AĞLARI VE YENİDEN ÖRNEKLEME METOTLARI İLE RUTİN KAN TESTLERİNE DAYALI COVID-19 TESPİTİ ; Covid-19 Detection Based on Routine Blood Tests With Deep Neural Networks and Resampling Methods |
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| المؤلفون: | Tokmak, Mahmut, Küçüksille, Ecir |
| بيانات النشر: | Konya Technical University |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Derin Sinir Ağları, Yeniden Örnekleme, COVID-19, Deep Neural Networks, Resampling |
| الوصف: | konjes ; DergiPark: 877805 ; Coronavirus (COVID-19) disease, which first appeared in December 2019 and caused a worldwide outbreak; is described as a viral disease caused by acute respiratory syndrome SARS-CoV-2.The current RRT-PCR test is used to detect COVID-19 disease. Due to long return time of this test, about 15-20% false-negative rates and expensive equipment, the detection method with the values of routine blood analyses can be considered as a faster and cheaper alternative. In this study, COVID-19 was tried to be detected by using Deep Neural Networks (DNN), one of the routine blood tests. Because there is class imbalance in the used data set, class imbalance has been eliminated by resampling methods and the performance of used algorithms has been evaluated. While resampling, SMOTE, ADASYN, Geometric SMOTE, Random UnderSampler, Random OverSampler algorithms were used. As a result of established model, the most successful result was obtained with the Random OverSampler algorithm, with an accuracy of 0.985 and an F1-score of 0.99. In addition, an application has been developed using PyQt to make predictions for new data to be entered and the contributions of used attributes to the model were determined and explained with the SHapley Additive Explanations (SHAP) technique. ; İlk olarak Aralık 2019’da ortaya çıkan ve dünya çapında bir salgına neden olan Koronavirüs (COVID- 19) hastalığı; akut solunum sendromu SARS-CoV-2’nin neden olduğu viral bir hastalık olarak tanımlanmaktadır. COVID-19 hastalığının tespiti için güncel olan rRT-PCR testi kullanılmaktadır. Bu tes- tin uzun geri dönüş süresi, -20 civarında yanlış negatif oranları ve pahalı ekipmanları olması nedeni- yle rutin kan incelemelerinin değerleri ile tespit yöntemi daha hızlı ve daha ucuz bir alternatif olarak değerlendirilebilmektedir. Bu çalışmada, rutin kan testlerinden Derin Sinir Ağları (DSA) kullanılarak COVID-19 tespit edilmeye çalışılmıştır. Kullanılan veri setinde sınıf dengesizliği olduğu için yeniden örnekleme yöntemleriyle sınıf ... |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | Turkish |
| Relation: | Konya Mühendislik Bilimleri Dergisi; Makale - Ulusal Hakemli Dergi - Başka Kurum Yazarı; https://hdl.handle.net/20.500.13091/2156; https://dergipark.org.tr/tr/pub/konjes/issue/62624/877805; https://doi.org/10.36306/konjes.877805; 522; 534; N/A |
| DOI: | 10.36306/konjes.877805 |
| الاتاحة: | https://hdl.handle.net/20.500.13091/2156 https://dergipark.org.tr/tr/download/article-file/1568053 https://dergipark.org.tr/tr/pub/konjes/issue/62624/877805 https://doi.org/10.36306/konjes.877805 |
| Rights: | open |
| رقم الانضمام: | edsbas.6B0AE675 |
| قاعدة البيانات: | BASE |
| DOI: | 10.36306/konjes.877805 |
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