This comprehensive overview focuses on the issues presented by the pandemic due to
COVID-19, understanding its spread and the wide-ranging effects of government-imposed …

Background: During the COVID-19 pandemic, there is a global demand for intelligent health
surveillance and diagnosis systems for patients with critical conditions, particularly those …

Abstract Machine learning (ML) has proved to be a prominent study field while solving
complex real-world problems. The whole globe has suffered and continues suffering from …

Most crowding measures in public transportation are usually aggregated at a service level.
This type of aggregation does not help to analyze microscopic behavior such as exposure …

In this paper, we study a type of disease that unknowingly spreads for a long time, but by
default, spreads only to a minimal population. This disease is not usually fatal and often …

Simple Summary This article proposes a comparative study between two models that can be
used by researchers for the analysis of survival data: Weibull regression and random …

The global crisis of the COVID-19 pandemic has highlighted the need for mathematical
models to inform public health strategies. The present study introduces a novel six …

The aim of this article is to systematically analyze the available literature on the efficacy and
validity of artificial intelligence (AI) applied to medical imaging techniques in the triage of …

Simple Summary In this research, we investigate the COVID-19 spread in Latin American
countries using time-series and epidemic models. We highlight the diverse outbreak …

Covariate-related response variables that are measured on the unit interval frequently arise
in diverse studies when index and proportion data are of interest. A regression on the mean …