Deep learning applications to combat the dissemination of COVID-19 disease: A review

Alsharif M., Alsharif Y., Yahya K., Alomari O., Albreem M., Jahid A.

European Review for Medical and Pharmacological Sciences, cilt.24, sa.21, ss.11455-11460, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Derleme
  • Cilt numarası: 24 Sayı: 21
  • Basım Tarihi: 2020
  • Doi Numarası: 10.26355/eurrev_202011_23640
  • Dergi Adı: European Review for Medical and Pharmacological Sciences
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, EMBASE, MEDLINE
  • Sayfa Sayıları: ss.11455-11460
  • Anahtar Kelimeler: AI, Artificial intelligence, Big data, Coronavirus pandemic, COVID-19, Machine learning, SARS-CoV-2
  • İstanbul Gelişim Üniversitesi Adresli: Evet

Özet

© 2020 Verduci Editore s.r.l. All rights reserved.Recent Coronavirus (COVID-19) is one of the respiratory diseases, and it is known as fast infectious ability. This dissemination can be decelerated by diagnosing and quarantining patients with COVID-19 at early stages, thereby saving numerous lives. Reverse transcription-polymerase chain reaction (RT-PCR) is known as one of the primary diagnostic tools. However, RT-PCR tests are costly and time-consuming; it also requires specific materials, equipment, and instruments. Moreover, most countries are suffering from a lack of testing kits because of limitations on budget and techniques. Thus, this standard method is not suitable to meet the requirements of fast detection and tracking during the COVID-19 pandemic, which motived to employ deep learning (DL)/ convolutional neural networks (CNNs) technology with X-ray and CT scans for efficient analysis and diagnostic. This study provides insight about the literature that discussed the deep learning technology and its various techniques that are recently developed to combat the dissemination of COVID-19 disease.