Sheng Long
Impact in
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- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- SARS-CoV-2 detection and testing
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- COVID-19 epidemiological studies
Papers in
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- Data Visualization and Analytics 1
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- COVID-19 Clinical Research Studies 1
- SARS-CoV-2 detection and testing 1
- Co-authors
- Randall J. Olsen (4 shared papers)Ryan Gadd (1 shared paper)Jimmy Gollihar (1 shared paper)James J. Davis (1 shared paper)Kristina Reppond (1 shared paper)Madison Shyer (1 shared paper)Rashi M. Thakur (1 shared paper)Robert Olson (1 shared paper)
- Journals
- Journal of Pathology Informatics (3 papers)Frontiers in Pharmacology (1 paper)American Journal of Clinical Pathology (1 paper)American Journal Of Pathology (1 paper)Journal of Pediatric Gastroenterology and Nutrition (1 paper)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Sheng Long
9 papers receiving 170 citations
Sheng Long's Hit Papers
Peers
Comparison fields: 5 of 52
- Infectious Diseases 95
- Modeling and Simulation 10
- Health Informatics 2
- Neurology 15
- Biological Psychiatry 2
Countries citing papers authored by Sheng Long
This map shows the geographic impact of Sheng Long's research. 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 Sheng Long with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sheng Long more than expected).
Fields of papers citing papers by Sheng Long
This network shows the impact of papers produced by Sheng Long. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sheng Long. The network helps show where Sheng Long may publish in the future.
Co-authors
The 25 scholars most cited alongside Sheng Long, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Signals of Significantly Increased Vaccine Breakthrough, Decreased Hospitalization Rates, and Less Severe Disease in Patients with Coronavirus Disease 2019 Caused by the Omicron Variant of Severe Acute Respiratory Syndrome Coronavirus 2 in Houston, Texas Hit paper breakdown → | 2022 | 130 |
| 2 | 2024 | 14 | |
| 3 | 2017 | 8 | |
| 4 | 2017 | 6 | |
| 5 | 2024 | 5 | |
| 6 | 1999 | 4 | |
| 7 | 2024 | 2 | |
| 8 | 2018 | 2 | |
| 9 | 2020 | 1 | |
| 10 | 2025 | 0 |
About Sheng Long
Sheng Long is a scholar working on Computer Vision and Pattern Recognition, Infectious Diseases, Surgery, Family Practice and Artificial Intelligence, having authored 10 papers that have together received 172 indexed citations. Recurring topics across this work include Hand Gesture Recognition Systems (1 paper), COVID-19 Clinical Research Studies (1 paper), Genomics and Rare Diseases (1 paper), Interactive and Immersive Displays (1 paper), SARS-CoV-2 detection and testing (1 paper), Healthcare Technology and Patient Monitoring (1 paper), Traditional Chinese Medicine Studies (1 paper) and Data Visualization and Analytics (1 paper). The work is most often cited by research in Infectious Diseases (95 citations), Modeling and Simulation (10 citations), Health Informatics (2 citations), Neurology (15 citations) and Biological Psychiatry (2 citations). Sheng Long has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Randall J. Olsen, Ryan Gadd, Jimmy Gollihar, James J. Davis, Kristina Reppond, Madison Shyer, Rashi M. Thakur, Robert Olson, Matthew Ojeda Saavedra and Akanksha Batajoo. Their work appears in journals such as Journal of Pathology Informatics, Frontiers in Pharmacology, American Journal of Clinical Pathology, American Journal Of Pathology and Journal of Pediatric Gastroenterology and Nutrition.
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.