Fernando Cava
Impact in
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- Meta-analysis and systematic reviews
- Nephrology top 10%
Papers in
- Physiology 16
- Clinical Laboratory Practices and Quality Control 15
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- Meta-analysis and systematic reviews 6
- Co-authors
- Carmen Perich (13 shared papers)Carmen Ricós (12 shared papers)Margarita Sánchez Simón (12 shared papers)Virtudes Álvarez (12 shared papers)Joana Minchinela (12 shared papers)Carmen Biosca (10 shared papers)José Vicente Garcı́a-Lario (6 shared papers)Angela Y. Jia (1 shared paper)
- Journals
- Clinical Chemistry and Laboratory Medicine (CCLM) (3 papers)Clinica Chimica Acta (2 papers)Biochemical Journal (2 papers)Journal of Clinical Pathology (2 papers)RMD Open (1 paper)
- Partner nations
- SpainUnited StatesUnited Kingdom
In The Last Decade
Fernando Cava
42 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 97
- Statistics, Probability and Uncertainty 111
- Nephrology 89
- Physiology 309
- Statistics and Probability 73
- Cancer Research 100
Countries citing papers authored by Fernando Cava
This map shows the geographic impact of Fernando Cava'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 Fernando Cava with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fernando Cava more than expected).
Fields of papers citing papers by Fernando Cava
This network shows the impact of papers produced by Fernando Cava. 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 Fernando Cava. The network helps show where Fernando Cava may publish in the future.
Co-authors
The 25 scholars most cited alongside Fernando Cava, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2007 | 166 | |
| 2 | 2004 | 135 | |
| 3 | 2012 | 130 | |
| 4 | 2014 | 86 | |
| 5 | 2009 | 54 | |
| 6 | 2020 | 49 | |
| 7 | 2012 | 46 | |
| 8 | 2000 | 44 | |
| 9 | 2015 | 42 | |
| 10 | 2019 | 37 | |
| 11 | 2001 | 28 | |
| 12 | 2013 | 25 | |
| 13 | 1992 | 23 | |
| 14 | 1996 | 18 | |
| 15 | 1992 | 18 | |
| 16 | 1989 | 17 | |
| 17 | 2016 | 16 | |
| 18 | 2010 | 14 | |
| 19 | 1991 | 12 | |
| 20 | 2004 | 10 |
About Fernando Cava
Fernando Cava is a scholar working on Physiology, Statistics, Probability and Uncertainty, Clinical Biochemistry, Statistics and Probability and Genetics, having authored 43 papers that have together received 1.1k indexed citations. Recurring topics across this work include Clinical Laboratory Practices and Quality Control (15 papers), Statistical Methods in Clinical Trials (6 papers), Meta-analysis and systematic reviews (6 papers), Metabolism and Genetic Disorders (5 papers), Cholesterol and Lipid Metabolism (4 papers), SARS-CoV-2 detection and testing (4 papers), Drug Transport and Resistance Mechanisms (4 papers) and Hemoglobinopathies and Related Disorders (3 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (111 citations), Nephrology (89 citations), Physiology (309 citations), Statistics and Probability (73 citations) and Cancer Research (100 citations). Fernando Cava has collaborated with scholars based in Spain, United States and United Kingdom. Frequent co-authors include Carmen Perich, Carmen Ricós, Margarita Sánchez Simón, Virtudes Álvarez, Joana Minchinela, Carmen Biosca, José Vicente Garcı́a-Lario, Angela Y. Jia, Jose Luis Alvarez Ossorio Fernandez and M. Álvarez-Múgica. Their work appears in journals such as Clinical Chemistry and Laboratory Medicine (CCLM), Clinica Chimica Acta, Biochemical Journal, Journal of Clinical Pathology and RMD 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.