Paloma Botella-Rocamora
- Cognitive Neuroscience top 10%
- Economics and Econometrics top 10%
- Artificial Intelligence top 10%
- Epidemiology
- Psychiatry and Mental health top 10%
- Co-authors
- Miguel A. Martínez‐BeneitoFrancisco Zamora-MartínezJuan PardoAntonio López‐QuílezSudipto BanerjeeFrancisco Javier Muñoz–AlmarazGregory A. WorrellSimone C. Bosshard
- Topics
- Data-Driven Disease Surveillance (5 papers)Statistical Methods and Inference (4 papers)Health disparities and outcomes (3 papers)
- Partner nations
- SpainUnited StatesAustralia
In The Last Decade
Paloma Botella-Rocamora
22 papers receiving 609 citations
Peers
Comparison fields: 5 of 109
- Cognitive Neuroscience 166
- Economics and Econometrics 99
- Artificial Intelligence 96
- Epidemiology 95
- Psychiatry and Mental health 93
Countries citing papers authored by Paloma Botella-Rocamora
This map shows the geographic impact of Paloma Botella-Rocamora'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 Paloma Botella-Rocamora with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paloma Botella-Rocamora more than expected).
Fields of papers citing papers by Paloma Botella-Rocamora
This network shows the impact of papers produced by Paloma Botella-Rocamora. 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 Paloma Botella-Rocamora. The network helps show where Paloma Botella-Rocamora may publish in the future.
Co-authorship network of co-authors of Paloma Botella-Rocamora
This figure shows the co-authorship network connecting the top 25 collaborators of Paloma Botella-Rocamora. A scholar is included among the top collaborators of Paloma Botella-Rocamora based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Paloma Botella-Rocamora. Paloma Botella-Rocamora is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 4 | |
| 3 | 7 | |
| 4 | 8 | |
| 5 | 37 | |
| 6 | 6 | |
| 7 | 5 | |
| 8 | 1 | |
| 9 | 25 | |
| 10 | 190 | |
| 11 | 37 | |
| 12 | 20 | |
| 13 | 93 | |
| 14 | 9 | |
| 15 | 7 | |
| 16 | 20 | |
| 17 | 3 | |
| 18 | Distribución de las enfermedades raras en España | 1 |
| 19 | 8 | |
| 20 | 83 |
About Paloma Botella-Rocamora
Paloma Botella-Rocamora is a scholar working on Statistics and Probability, Health and Modeling and Simulation, having authored 22 papers that have together received 620 indexed citations. Recurring topics across this work include Data-Driven Disease Surveillance (5 papers), Statistical Methods and Inference (4 papers) and Health disparities and outcomes (3 papers). The work is most often cited by research in Statistics and Probability (80 citations), Cognitive Neuroscience (166 citations) and Signal Processing (83 citations). Paloma Botella-Rocamora has collaborated with scholars based in Spain, United States and Australia. Frequent co-authors include Miguel A. Martínez‐Beneito, Francisco Zamora-Martínez, Juan Pardo, Antonio López‐Quílez, Sudipto Banerjee, Francisco Javier Muñoz–Almaraz, Gregory A. Worrell, Simone C. Bosshard, Charles H. Vite and Edward E. Patterson. Their work appears in journals such as PLoS ONE, Brain and Sensors.
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.