To search, Click below search items. |
| All Published Papers Search Service |
|
|
|
Title |
Utilization of machine learning algorithms in COVID-19 classification and prediction: A review |
|
Author |
Shahad Abdelmuniem Mohamed Awadelkarim, Abdelrahman Elsharif Karrar, |
| Citation |
Vol. 25 No. 3 pp. 81-92 |
|
Abstract |
Since 2019, more than 600 million people worldwide have contracted the rapidly growing COVID-19 disease. For healthy people to be protected and for patients to receive the best medical care, early COVID-19 virus detection is essential. Furthermore, due to the similarities between the symptoms of COVID and pneumonia, it was somewhat challenging to classify them. This survey reveals notable findings in several studies that combined many machine learning algorithms and the accuracy rates frequently utilized when using massive datasets of CT scans and X-ray images. |
|
Keywords |
COVID-19, Pneumonia, Classification, Prediction, Machine Learning |
|
URL |
