A new composite approach for COVID-19 detection in X-ray images using deep features

ÖZCAN T.

APPLIED SOFT COMPUTING, cilt.111, 2021 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 111
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1016/j.asoc.2021.107669
  • Dergi Adı: APPLIED SOFT COMPUTING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, INSPEC
  • Anahtar Kelimeler: COVID-19 detection in X-ray images, Pre-trained models, Feature extraction, Deep features, Feature fusion, Data processing, OPTIMIZATION, RECOGNITION, FUSION
  • Erciyes Üniversitesi Adresli: Evet

Özet

The new type of coronavirus, COVID 19, appeared in China at the end of 2019. It has become a pandemic that is spreading all over the world in a very short time. The detection of this disease, which has serious health and socio-economic damages, is of vital importance. COVID-19 detection is performed by applying PCR and serological tests. Additionally, COVID detection is possible using X-ray and computed tomography images. Disease detection has an important position in scientific researches that includes artificial intelligence methods.