Application of Machine Learning for the Pbkp_rediction of Covid19 through Classification Techniques and Supervised Learning

Abstract:

In January 2020, in the city of Wuhan in China, a highly dangerous disease for humans appeared, cataloged as COVID-19 and caused by a virus called SARS-CoV-2; This disease spread from Asia to Europe and then spread throughout the American continent, causing a pandemic that to this day continues to cause irreparable damage. Currently the virus has mutated, and its variants continue to congest health systems in all parts of the world. The spread of the virus has generated information that is available on public research-oriented portals, and that is available for scientists and researchers to have the necessary information so that they can develop strategies to face and stop the disease. Using machine learning techniques, a pbkp_rediction model has been created, which by applying supervised learning performs an analysis of historical data and has learned to identify patterns, managing to identify the disease.

Año de publicación:

2022

Keywords:

• ALGORITHMS
• Machine learning
• Supervised learning
• covid-19

Fuente:

scopus