Acute Myocardial Infarction after Laboratory-Confirmed Influenza Infection
Impact in
- Epidemiology 304
Countries where authors are citing Acute Myocardial Infarction after Laboratory-Confirmed Influenza Infection
This map shows the geographic impact of Acute Myocardial Infarction after Laboratory-Confirmed Influenza Infection. 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 Acute Myocardial Infarction after Laboratory-Confirmed Influenza Infection with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Acute Myocardial Infarction after Laboratory-Confirmed Influenza Infection more than expected).
Fields of papers citing Acute Myocardial Infarction after Laboratory-Confirmed Influenza Infection
This network shows the impact of Acute Myocardial Infarction after Laboratory-Confirmed Influenza Infection. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Acute Myocardial Infarction after Laboratory-Confirmed Influenza Infection.
About Acute Myocardial Infarction after Laboratory-Confirmed Influenza Infection
This paper, published in 2018, received 798 indexed citations . Written by Jeffrey C. Kwong, Kevin L. Schwartz, Michael A. Campitelli, Hannah Chung, Natasha S. Crowcroft, Timothy Karnauchow, Kevin Katz, Dennis T. Ko, Allison McGeer and Dayre McNally. It is primarily cited by scholars working on Epidemiology (304 citations), Infectious Diseases (275 citations), Cardiology and Cardiovascular Medicine (151 citations), Neurology (125 citations) and Oncology (94 citations). Published in New England Journal of Medicine.
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/10.1056/nejmoa1702090.