Srinivas Murthy

113 papers receiving 2.7k citations

Srinivas Murthy's Hit Papers

Care for Critically Ill Patients With COVID-19 2020 · 524 citations
5240+2+4Years since publication100200300400500

Peers

Srinivas Murthy
Comparison fields: 5 of 156
  • Critical Care and Intensive Care Medicine 164
  • Infectious Diseases 548
  • Modeling and Simulation 114
  • Neurology 293
  • Emergency Medical Services 124
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Citations per field
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Citations per year

Countries citing papers authored by Srinivas Murthy

Since Specialization
Citations

This map shows the geographic impact of Srinivas Murthy'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 Srinivas Murthy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Srinivas Murthy more than expected).

Fields of papers citing papers by Srinivas Murthy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Srinivas Murthy. 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 Srinivas Murthy. The network helps show where Srinivas Murthy may publish in the future.

Co-authors

The 25 scholars most cited alongside Srinivas Murthy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Srinivas Murthy Line = papers co-authored together Srinivas Murthy links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 134 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Care for Critically Ill Patients With COVID-19
Hit paper breakdown →
2020524
2 2002229
3 2015229
4 2020206
5 2012109
6 2012102
7 201279
8 202074
9 201372
10 202257
11 201256
12 202054
13 202048
14 202045
15 202043
16 201342
17 201538
18 202027
19 201927
20 202127

About Srinivas Murthy

Srinivas Murthy is a scholar working on Infectious Diseases, Epidemiology, Public Health, Environmental and Occupational Health, Emergency Medical Services and General Health Professions, having authored 134 papers that have together received 2.8k indexed citations. Recurring topics across this work include Sepsis Diagnosis and Treatment (16 papers), COVID-19 Clinical Research Studies (13 papers), Respiratory Support and Mechanisms (7 papers), Disaster Response and Management (6 papers), Viral Infections and Outbreaks Research (6 papers), Climate Change and Health Impacts (5 papers), Cardiac Arrest and Resuscitation (5 papers) and Intensive Care Unit Cognitive Disorders (4 papers). The work is most often cited by research in Critical Care and Intensive Care Medicine (164 citations), Infectious Diseases (548 citations), Modeling and Simulation (114 citations), Neurology (293 citations) and Emergency Medical Services (124 citations). Srinivas Murthy has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Robert Fowler, Charles D. Gomersall, Neill K. J. Adhikari, Aleksandra Leligdowicz, Yaseen M. Arabi, Steve Webb, Michael E. Cohen, Rohit Bakshi, Howard Faden and Hannah Wunsch. Their work appears in journals such as Canadian Journal of Anesthesia/Journal canadien d anesthésie, Pediatric Critical Care Medicine, PLoS ONE, Critical Care Medicine and BMJ Open.

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.

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