State-of-the-Art Review on the Models, Techniques, and Datasets to Diagnose COVID-19 Disease

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Author(s): Vetrithangam D. (Chandigarh University, India), Naresh Kumar Pegada (K.G. Reddy College of Engineering and Technology, India), Himabindu R. (Mallareddy University, India), Arunadevi B. (Dr. N.G.P. Institute of Technology, India)and Ramesh Kumar A. (K.S. Rangasamy College of Technology, India)
Copyright: 2024
Pages: 26
Source title: Research Anthology on Bioinformatics, Genomics, and Computational Biology
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/979-8-3693-3026-5.ch065

Keywords: Bioinformatics / Medical Information Science Reference / Medicine & Healthcare

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Abstract

The present corona virus disease outbreak of 2019 is a rapidly spreading illness caused by the novel serious acute respiratory syndrome coronavirus2 (SARS-Cov2). France has the highest rates of infection, morbidity, and mortality, and is among the nations most impacted by the disease, along with the United States, India, Brazil, and Russia. Since early January 2022, thousands of articles have been published on COVID-19. The majority of these articles agreed with descriptions of the mode of transmission, spread, duration, and severity of the illness; models or techniques used to diagnose the COVID-19 disease; and vaccine status in various locations. Thus, this review completely discusses the highest analytical aspects of COVID-19, including various classification, segmentation, prediction, and feature selection techniques to diagnose, detect, and predict the Covid-19 disease. This review chapter will surely help researchers to choose the techniques and datasets for effective diagnosis and evaluation.

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State-of-the-Art Review on the Models, Techniques, and Datasets to Diagnose COVID-19 Disease

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