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

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Küçük Resim

Tarih

2020

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

VERDUCI PUBLISHER, VIA GREGORIO VII, ROME 186-00165, ITALY

Erişim Hakkı

info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivs 3.0 United States

Özet

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 (RTPCR) 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.

Açıklama

Anahtar Kelimeler

Artificial intelligence, Coronavirus pandemic, AI, SARS-CoV-2, Machine learning, Big data, COVID-19

Kaynak

European Review for Medical and Pharmacological Sciences

WoS Q Değeri

Q2

Scopus Q Değeri

Q2

Cilt

24

Sayı

21

Künye