Multiclass Supervised Learning Approach for SAR-COV2 Severity and Scope Prediction: SC2SSP Framework - Shaik Khasim Saheb; B. Narayanan; T.V. Narayana Rao (Frontiers in Biomedical Technologies)
Purpose: Identifying high-risk areas for the virus or the potential for the technique to be applied to this infectious disease might be difficult. The existing tools being used for predicting viruses exhibit various limitations. The severe pneumonia caused by the rapidly spreading coronavirus disease (COVID-19) is predicted to have a significant negative impact on the healthcare sector. Accurate treatment requires an urgent need for early diagnosis, which reduces pressure on the healthcare system. Computed Tomography (CT) scan and Chest X-Ray (CXR) are some of the standard image diagnoses. Although a CT scan is the most common method for diagnosis, CXR is the most frequently utilized since it is more accessible, quicker, and less expensive.