Coronavirus Disease (COVID-19): A Machine Learning Bibliometric Analysis

FRANCESCA DE FELICE; ANTONELLA POLIMENI

doi:10.21873/invivo.11951

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Coronavirus Disease (COVID-19): A Machine Learning Bibliometric Analysis

FRANCESCA DE FELICE and ANTONELLA POLIMENI

In Vivo June 2020, 34 (3 suppl) 1613-1617; DOI: https://doi.org/10.21873/invivo.11951

FRANCESCA DE FELICE

1Department of Radiotherapy, Policlinico Umberto I “Sapienza” University of Rome, Rome, Italy

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For correspondence: fradefelice@hotmail.it

ANTONELLA POLIMENI

2Department of Oral and Maxillo Facial Sciences, Policlinico Umberto I, “Sapienza” University of Rome, Rome, Italy

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Figure 1.
Country collaboration.
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Figure 2.
The top twenty relevant affiliations.
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Figure 3.
Summary plot matching the most productive countries (on the left), the most relevant author keywords (in the middle) and the most relevant sources (on the right).

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In Vivo

Vol. 34, Issue 3 suppl

June 2020

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