Features, Evaluation and Treatment Coronavirus (COVID-19)
Impact in
- Infectious Diseases 1.0k
- Neurology 330
Classified as
- Journal
- StatPearls
In The Last Decade
doi.org/w3268470 →Countries where authors are citing Features, Evaluation and Treatment Coronavirus (COVID-19)
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)
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).
About Features, Evaluation and Treatment Coronavirus (COVID-19)
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), Clinical Psychology (297 citations), Modeling and Simulation (232 citations) and Radiology, Nuclear Medicine and Imaging (222 citations). Published in StatPearls.
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/w3268470.