Humberto Carrillo-Calvet

TL;DR: It is suggested that observers see different things when looking at the samples in the microscope; a situation that significantly diminishes the performance of these classifiers in diagnosing such a disease.

TL;DR: The neural network technique proves to be a worthy scientometric data mining and visualization tool which automatically carries out multiparametric scientometric characterizations of the production profiles of the 50 most productive Mexican Higher Education Institutions (in Scopus database).

TL;DR: There are considerable differences in all tests when a specific classifiers uses the single-observer dataset compared to those when this same classifier uses the multiple-ob server dataset, suggesting that different observers see different things: a problem known as interobserver variability.

TL;DR: The scientific output after COVID-19 was analyzed and contrasted it with studies published in the aftermath of seven epidemics/pandemics, showing the broadest subject coverage, which is clearly a consequence of its social, economic, and political impact.

TL;DR: Literary on A. aegypti during the last 10 years showed an exponential growth, associated with the identification of mosquitos in new environments, as well as the appearance of outbreaks related to diseases transmitted by this vector.