Bibliometric Analysis: Nanotechnology and COVID-19.

Background: COVID-19 pandemic information is critical to study it further, but the virus has still not been confined. In addition, even if there is no longer any threat, more knowledge may be gathered from these resources.

Methods: The data used in this study was gathered from several scientific areas and the links between them.

A multipurpose machine learning approach to predict COVID-19 negative prognosis in São Paulo, Brazil.

The new coronavirus disease (COVID-19) is a challenge for clinical decision-making and the effective allocation of healthcare resources. An accurate prognostic assessment is necessary to improve survival of patients, especially in developing countries. This study proposes to predict the risk of developing critical conditions in COVID-19 patients by training multipurpose algorithms.