Detection and Classification of COVID-19 Using Machine Learning Techniques: A Review

  • Received
    December 28, 2022
  • Revised
    February 10, 2023
  • Accepted
    February 11, 2023
  • Published
    February 11, 2023


  • Ashraf Abdulmunim Abdulmajeed
  • Nada N. Saleem


The pandemic COVID19, caused by a member of the coronavirus family (SARS-COV-2), occurred in Wuhan in 2019 and can cause the severe acute respiratory syndrome, fatal complications, and death. One of the main problems of the twenty-first century is coronavirus illness (COVID-19), which SARS-CoV-2 brings on. This virus, which has killed 6,654,361 people globally and infected 649,605,347 people, is currently causing widespread global conflict. Due to the high infection incidence in China and other nations within a short time, the WHO (World Health Organization) declared it a pandemic on February 11, 2020. Numerous individuals perished as a result of the COVID-19 pandemic epidemic. This virus has already infected millions of individuals, and new infections are occurring every day. Researchers are attempting to employ medical imaging like CT and X-ray images to identify COVID-19 With the use of modern AI technologies both the cost and time required to run a traditional RT-PCR test for detection is prohibitive. In order to combat the impacts of the new coronavirus illness, this research presents a thorough assessment of using artificial intelligence (AI) in the form of machine learning (ML) and deep learning (DL) approaches in identifying (COVID-19). The primary objectives of this paper lie in identifying the broad and important outlines of the process of systematically researching the mechanisms of detection and classification of the Coronavirus through a review of a group of researchers; in addition, to compile the most used methods for independently identifying COVID-19 from medical images, and knowing the data sources of cross-sectional images. The researchers relied on Lung and x-rays in identifying the process, Furthermore, to discussing the accuracy of the results of the research through a review of the machine learning and general learning techniques used by the researchers are discussed. So, a novice researcher can evaluate prior works and come up with a better solution.


COVID-19, Deep Learning, Medical Image, Artificial intelligence, coronavirus, computed tomography, CT images, Machine learning, X-ray.


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