Skip to main content

Main menu

  • Home
  • Current Issue
  • Archive
  • Info for
    • Authors
    • Editorial Policies
    • Advertisers
    • Editorial Board
  • Other Publications
    • Anticancer Research
    • Cancer Genomics & Proteomics
    • Cancer Diagnosis & Prognosis
  • More
    • IIAR
    • Conferences
  • About Us
    • General Policy
    • Contact
  • Other Publications
    • In Vivo
    • Anticancer Research
    • Cancer Genomics & Proteomics

User menu

  • Register
  • Subscribe
  • My alerts
  • Log in
  • My Cart

Search

  • Advanced search
In Vivo
  • Other Publications
    • In Vivo
    • Anticancer Research
    • Cancer Genomics & Proteomics
  • Register
  • Subscribe
  • My alerts
  • Log in
  • My Cart
In Vivo

Advanced Search

  • Home
  • Current Issue
  • Archive
  • Info for
    • Authors
    • Editorial Policies
    • Advertisers
    • Editorial Board
  • Other Publications
    • Anticancer Research
    • Cancer Genomics & Proteomics
    • Cancer Diagnosis & Prognosis
  • More
    • IIAR
    • Conferences
  • About Us
    • General Policy
    • Contact
  • Visit iiar on Facebook
  • Follow us on Linkedin
Review ArticleReviewsR

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
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: fradefelice@hotmail.it
ANTONELLA POLIMENI
2Department of Oral and Maxillo Facial Sciences, Policlinico Umberto I, “Sapienza” University of Rome, Rome, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

Article Figures & Data

Figures

  • Tables
  • Figure 1.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 1.

    Country collaboration.

  • Figure 2.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 2.

    The top twenty relevant affiliations.

  • Figure 3.
    • Download figure
    • Open in new tab
    • Download powerpoint
    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).

Tables

  • Figures
  • Table I.
PreviousNext
Back to top

In this issue

In Vivo
Vol. 34, Issue 3 suppl
June 2020
  • Table of Contents
  • Table of Contents (PDF)
  • Index by author
  • Back Matter (PDF)
  • Ed Board (PDF)
  • Front Matter (PDF)
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on In Vivo.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Coronavirus Disease (COVID-19): A Machine Learning Bibliometric Analysis
(Your Name) has sent you a message from In Vivo
(Your Name) thought you would like to see the In Vivo web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
9 + 3 =
Solve this simple math problem and enter the result. E.g. for 1+3, enter 4.
Citation Tools
Coronavirus Disease (COVID-19): A Machine Learning Bibliometric Analysis
FRANCESCA DE FELICE, ANTONELLA POLIMENI
In Vivo Jun 2020, 34 (3 suppl) 1613-1617; DOI: 10.21873/invivo.11951

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Reprints and Permissions
Share
Coronavirus Disease (COVID-19): A Machine Learning Bibliometric Analysis
FRANCESCA DE FELICE, ANTONELLA POLIMENI
In Vivo Jun 2020, 34 (3 suppl) 1613-1617; DOI: 10.21873/invivo.11951
Reddit logo Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Materials and Methods
    • Results
    • Discussion
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • PDF

Related Articles

  • No related articles found.
  • PubMed
  • Google Scholar

Cited By...

  • Bibliometric analysis of COVID-19 literature
  • The multidisciplinary nature of COVID-19 research
  • Google Scholar

More in this TOC Section

  • Research Progress on the Microregulatory Mechanisms of Fertilization: A Review
  • Gastric Cancer Invading the Pancreas: A Review of the Role of Pancreatectomy
  • Circulating microRNAs and Clinicopathological Findings of Papillary Thyroid Cancer: A Systematic Review
Show more Reviews

Similar Articles

Keywords

  • COVID-19
  • coronavirus
  • bibliometric analysis
  • Machine learning
  • management
In Vivo

© 2023 In Vivo

Powered by HighWire