The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
State-of-the-Art Review on the Models, Techniques, and Datasets to Diagnose COVID-19 Disease
|
|
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: 2023
Pages: 26
Source title:
Handbook of Research on AI and Knowledge Engineering for Real-Time Business Intelligence
Source Author(s)/Editor(s): Kamal Kant Hiran (Sir Padampat Singhania University, India & Lincoln University College, Malaysia), K. Hemachandran (Woxsen University, India), Anil Pise (University of the Witwatersrand, South Africa)and B. Justus Rabi (Christian College of Engineering and Technology, India)
DOI: 10.4018/978-1-6684-6519-6.ch014
Purchase
|
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.
Related Content
|
Dina Darwish.
© 2024.
48 pages.
|
|
Dina Darwish.
© 2024.
51 pages.
|
|
Smrity Prasad, Kashvi Prawal.
© 2024.
19 pages.
|
|
Jignesh Patil, Sharmila Rathod.
© 2024.
17 pages.
|
|
Ganesh B. Regulwar, Ashish Mahalle, Raju Pawar, Swati K. Shamkuwar, Priti Roshan Kakde, Swati Tiwari.
© 2024.
23 pages.
|
|
Pranali Dhawas, Abhishek Dhore, Dhananjay Bhagat, Ritu Dorlikar Pawar, Ashwini Kukade, Kamlesh Kalbande.
© 2024.
24 pages.
|
|
Pranali Dhawas, Minakshi Ashok Ramteke, Aarti Thakur, Poonam Vijay Polshetwar, Ramadevi Vitthal Salunkhe, Dhananjay Bhagat.
© 2024.
26 pages.
|
|
|