David Moriña

1.2k citations
62 papers · 690 · h-index 16

Impact in

Papers in

David Moriña

59 papers receiving 674 citations

Peers

David Moriña
Comparison fields: 5 of 123
  • Modeling and Simulation 49
  • Statistics and Probability 69
  • Public Health, Environmental and Occupational Health 103
  • Finance 39
  • General Health Professions 80
Replace Airlane Pereira Alencar with:
Airlane Pereira Alencar Brazil
Pascale Tubert‐Bitter France
Karla Diaz‐Ordaz United Kingdom
Hyokyoung G. Hong United States
Sudhir Jadhav India
Dan Xiao China
Keewhan Choi United States
Thomas W. Carton United States
Christian Léonard United States
Maximilian Salcher‐Konrad United Kingdom
David Moriña relative to Airlane Pereira Alencar Brazil Airlane Pereira Alencar's profile →
Citations per field
00.5×2.6×
Airlane Pereira Alencar · 1×
Citations per year

Countries citing papers authored by David Moriña

Since Specialization
Citations

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

Fields of papers citing papers by David Moriña

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside David Moriña, 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 David Moriña Line = papers co-authored together David Moriña links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201455
2 201451
3 201148
4 202031
5 201428
6 201927
7 201624
8 201922
9 201921
10 201121
11 202020
12 201719
13 201819
14 201418
15 201418
16 201617
17
Prevalence of visual impairment in El Salvador: inequalities in educational level and occupational status.
201415
18 201914
19 201514
20 201813

About David Moriña

David Moriña is a scholar working on General Health Professions, Epidemiology, Statistics and Probability, Artificial Intelligence and Finance, having authored 62 papers that have together received 690 indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (7 papers), Workplace Health and Well-being (6 papers), Statistical Methods and Inference (5 papers), COVID-19 epidemiological studies (4 papers), Cervical Cancer and HPV Research (4 papers), Bayesian Methods and Mixture Models (4 papers), Financial Risk and Volatility Modeling (4 papers) and Radiation Dose and Imaging (4 papers). The work is most often cited by research in Modeling and Simulation (49 citations), Statistics and Probability (69 citations), Public Health, Environmental and Occupational Health (103 citations), Finance (39 citations) and General Health Professions (80 citations). David Moriña has collaborated with scholars based in Spain, United States and Germany. Frequent co-authors include Pedro Puig, Albert Navarro, Rosa Solà, Lucía Tarro, Elisabet Llauradó, Montse Giralt, Alexandre Hyafil, Amanda Fernández‐Fontelo, Victoria Arija and Anna Vilella. Their work appears in journals such as PLoS ONE, Statistics in Medicine, The R Journal, Scientific Reports and Journal of Radiological Protection.

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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