I Clement'
Impact in
- Infectious Diseases top 2%
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
- Genetics top 5%
- Genetic Associations and Epidemiology
Papers in
-
- COVID-19 Clinical Research Studies 9
- Genetics 5
- Genetic Associations and Epidemiology 5
- Journals
- JAMA (9 papers)Nature (4 papers)The Lancet (3 papers)JAMA Network Open (1 paper)Intensive Care Medicine Experimental (1 paper)
- Partner nations
- United Kingdom
In The Last Decade
I Clement'
24 papers receiving 2.1k citations
I Clement''s Hit Papers
Peers
Comparison fields: 5 of 94
- Infectious Diseases 1k
- Genetics 512
- Neurology 98
- Immunology 118
- Internal Medicine 18
Countries citing papers authored by I Clement'
This map shows the geographic impact of I Clement''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 I Clement' with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites I Clement' more than expected).
Fields of papers citing papers by I Clement'
This network shows the impact of papers produced by I Clement'. 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 I Clement'. The network helps show where I Clement' may publish in the future.
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All Works
Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Mapping the human genetic architecture of COVID-19 Hit paper breakdown → | 2021 | 656 |
| 2 | Whole-genome sequencing reveals host factors underlying critical COVID-19 Hit paper breakdown → | 2022 | 233 |
| 3 | Baricitinib in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial and updated meta-analysis Hit paper breakdown → | 2022 | 231 |
| 4 | 2021 | 166 | |
| 5 | 2019 | 137 | |
| 6 | GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19 Hit paper breakdown → | 2023 | 125 |
| 7 | 2022 | 105 | |
| 8 | 2022 | 100 | |
| 9 | Higher dose corticosteroids in patients admitted to hospital with COVID-19 who are hypoxic but not requiring ventilatory support (RECOVERY): a randomised, controlled, open-label, platform trial Hit paper breakdown → | 2023 | 84 |
| 10 | 2023 | 62 | |
| 11 | 2023 | 60 | |
| 12 | 2023 | 46 | |
| 13 | 2024 | 45 | |
| 14 | 2023 | 34 | |
| 15 | 2023 | 25 | |
| 16 | 2024 | 24 | |
| 17 | Dexmedetomidine- or Clonidine-Based Sedation Compared With Propofol in Critically Ill Patients Hit paper breakdown → | 2025 | 17 |
| 18 | 2025 | 13 | |
| 19 | 2019 | 8 | |
| 20 | 2024 | 8 |
About I Clement'
I Clement' is a scholar working on Infectious Diseases, Genetics, Critical Care and Intensive Care Medicine, Anesthesiology and Pain Medicine and Epidemiology, having authored 25 papers that have together received 2.2k indexed citations. Recurring topics across this work include COVID-19 Clinical Research Studies (9 papers), Genetic Associations and Epidemiology (5 papers), Sepsis Diagnosis and Treatment (4 papers), Innovations in Medical Education (2 papers), Intensive Care Unit Cognitive Disorders (2 papers), Reflective Practices in Education (2 papers), Anesthesia and Sedative Agents (2 papers) and Patient Satisfaction in Healthcare (1 paper). The work is most often cited by research in Infectious Diseases (1k citations), Genetics (512 citations), Neurology (98 citations), Immunology (118 citations) and Internal Medicine (18 citations). I Clement' has collaborated with scholars based in United Kingdom. Their work appears in journals such as JAMA, Nature, The Lancet, JAMA Network Open and Intensive Care Medicine Experimental.
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.