Features, Evaluation and Treatment Coronavirus (COVID-19)

1.9k indexed citations

Abstract

loading...

About

This paper, published in 2020, received 1.9k indexed citations. Written by Marco Cascella, Michael Rajnik, Arturo Cuomo, Scott C. Dulebohn and Raffaela Di Napoli covering the research area of Clinical Psychology and Infectious Diseases. It is primarily cited by scholars working on Infectious Diseases (1.0k citations), Neurology (330 citations) and Clinical Psychology (297 citations). Published in StatPearls.

In The Last Decade

doi.org/w3834671 →

Countries where authors are citing Features, Evaluation and Treatment Coronavirus (COVID-19)

Specialization
Citations

This map shows the geographic impact of Features, Evaluation and Treatment Coronavirus (COVID-19). It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Features, Evaluation and Treatment Coronavirus (COVID-19) with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Features, Evaluation and Treatment Coronavirus (COVID-19) more than expected).

Fields of papers citing Features, Evaluation and Treatment Coronavirus (COVID-19)

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Features, Evaluation and Treatment Coronavirus (COVID-19). Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Features, Evaluation and Treatment Coronavirus (COVID-19).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

This paper is also available at doi.org/w3834671.

Explore hit-papers with similar magnitude of impact

Rankless by CCL
2026