Redirigiendo al acceso original de articulo en 15 segundos...
Inicio  /  Information  /  Vol: 11 Par: 9 (2020)  /  Artículo
ARTÍCULO
TITULO

The Role of Artificial Intelligence, MLR and Statistical Analysis in Investigations about the Correlation of Swab Tests and Stress on Health Care Systems by COVID-19

Behzad Pirouz    
Hana Javadi Nejad    
Galileo Violini and Behrouz Pirouz    

Resumen

The outbreak of the new Coronavirus (COVID-19) pandemic has prompted investigations on various aspects. This research aims to study the possible correlation between the numbers of swab tests and the trend of confirmed cases of infection, while paying particular attention to the sickness level. The study is carried out in relation to the Italian case, but the result is of more general importance, particularly for countries with limited ICU (intensive care units) availability. The statistical analysis showed that, by increasing the number of tests, the trend of home isolation cases was positive. However, the trend of mild cases admitted to hospitals, intensive case cases, and daily deaths were all negative. The result of the statistical analysis provided the basis for an AI study by ANN. In addition, the results were validated using a multivariate linear regression (MLR) approach. Our main result was to identify a significant statistical effect of a reduction of pressure on the health care system due to an increase in tests. The relevance of this result is not confined to the COVID-19 outbreak, because the high demand of hospitalizations and ICU treatments due to this pandemic has an indirect effect on the possibility of guaranteeing an adequate treatment for other high-fatality diseases, such as, e.g., cardiological and oncological ones. Our results show that swab testing may play a significant role in decreasing stress on the health system. Therefore, this case study is relevant, in particular, for plans to control the pandemic in countries with a limited capacity for admissions to ICU units.

 Artículos similares

       
 
Romy Müller, Marcel Dürschmidt, Julian Ullrich, Carsten Knoll, Sascha Weber and Steffen Seitz    
Deep neural networks are powerful image classifiers but do they attend to similar image areas as humans? While previous studies have investigated how this similarity is shaped by technological factors, little is known about the role of factors that affec... ver más
Revista: Applied Sciences

 
Fátima Trindade Neves, Manuela Aparicio and Miguel de Castro Neto    
In the rapidly evolving landscape of urban development, where smart cities increasingly rely on artificial intelligence (AI) solutions to address complex challenges, using AI to accurately predict real estate prices becomes a multifaceted and crucial tas... ver más
Revista: Applied Sciences

 
Carlos Serôdio, Pedro Mestre, Jorge Cabral, Monica Gomes and Frederico Branco    
In the context of Industry 4.0, this paper explores the vital role of advanced technologies, including Cyber?Physical Systems (CPS), Big Data, Internet of Things (IoT), digital twins, and Artificial Intelligence (AI), in enhancing data valorization and m... ver más
Revista: Applied Sciences

 
Enrica Serretiello, Annafrancesca Smimmo, Andrea Ballini, Domenico Parmeggiani, Massimo Agresti, Paola Bassi, Giancarlo Moccia, Antonella Sciarra, Alessandra De Angelis, Paola Della Monica, Maria Michela Marino and Marina Di Domenico    
Breast cancer (BC) caused 685,000 deaths globally in 2020, earning the title of the most common type of tumor among females. With a multifactorial genesis, BC is influenced by several factors such as age, genetic and epigenetic predisposition, and an ind... ver más
Revista: Applied Sciences

 
Qiang Han, Tiansong Qi and Mosammat Mustari Khanaum    
Urbanization and climate change exacerbate groundwater overexploitation and urban flooding. The infiltration basin plays a significant role in protecting groundwater resources because it is a prevalent technology of managed aquifer recharge. It could als... ver más
Revista: Water