Fernando Cava

39 papers receiving 894 citations

Peers

Fernando Cava
Comparison fields: 5 of 102
  • Statistics, Probability and Uncertainty 161
  • Nephrology 106
  • Physiology 345
  • Statistics and Probability 98
  • Cancer Research 115
Replace Ole Blaabjerg with:
Ole Blaabjerg Denmark
Finlay MacKenzie United Kingdom
Dana Bailey Canada
P. J. Brombacher Netherlands
A. Uldall Denmark
Lorin M Bachmann United States
Douglas Chesher Australia
Tester F. Ashavaid India
Huub H. van Rossum Netherlands
Trefor Higgins Canada
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Citations per year

Countries citing papers authored by Fernando Cava

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007150
2 2012128
3 2004118
4 201473
5 200949
6 201244
7 200042
8 201538
9 201930
10 200127
11 199221
12 201319
13 199216
14 199616
15 198916
16 201615
17 201013
18 199110
19 20159
20 20048

About Fernando Cava

Fernando Cava is a scholar working on Statistics, Probability and Uncertainty, Clinical Biochemistry, Statistics and Probability, Medical Laboratory Technology and Physiology, having authored 39 papers that have together received 927 indexed citations. Recurring topics across this work include Clinical Laboratory Practices and Quality Control (16 papers), Meta-analysis and systematic reviews (8 papers), Statistical Methods in Clinical Trials (7 papers), Metabolism and Genetic Disorders (4 papers), Cholesterol and Lipid Metabolism (4 papers), Drug Transport and Resistance Mechanisms (4 papers), Fatty Acid Research and Health (3 papers) and Hemoglobinopathies and Related Disorders (3 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (161 citations), Nephrology (106 citations), Physiology (345 citations), Statistics and Probability (98 citations) and Cancer Research (115 citations). Fernando Cava has collaborated with scholars based in Spain, United Kingdom and United States. Frequent co-authors include Carmen Perich, Joana Minchinela, Carmen Ricós, Margarita Sánchez Simón, Virtudes Álvarez, Carmen Biosca, Rodrigo García-Baquero, Marta Sänchez‐Carbayo, Angela Y. Jia and Patricia Puerta. Their work appears in journals such as Clinical Chemistry and Laboratory Medicine (CCLM), Journal of Clinical Pathology, Biochemical Journal, Clinica Chimica Acta and Journal of Agricultural and Food Chemistry.

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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