Antonio Miranda-Escalada

106 total papers · 570 total citations
6 papers, 121 citations indexed

About

Antonio Miranda-Escalada is a scholar working on Molecular Biology, General Health Professions and Artificial Intelligence. According to data from OpenAlex, Antonio Miranda-Escalada has authored 6 papers receiving a total of 121 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Molecular Biology, 2 papers in General Health Professions and 2 papers in Artificial Intelligence. Recurrent topics in Antonio Miranda-Escalada's work include Biomedical Text Mining and Ontologies (3 papers), Topic Modeling (2 papers) and Interpreting and Communication in Healthcare (2 papers). Antonio Miranda-Escalada is often cited by papers focused on Biomedical Text Mining and Ontologies (3 papers), Topic Modeling (2 papers) and Interpreting and Communication in Healthcare (2 papers). Antonio Miranda-Escalada collaborates with scholars based in Spain, Ireland and Finland. Antonio Miranda-Escalada's co-authors include Martin Krallinger, Aitor González-Agirre, Jordi Armengol-Estapé, Graciela Gonzalez‐Hernandez, Ilseyar Alimova, Ari Z Klein, Davy Weissenbacher, Zulfat Miftahutdinov, Karen O’Connor and Abeed Sarker and has published in prestigious journals such as Database, Procesamiento del lenguaje natural and CLEF (Working Notes).

In The Last Decade

Antonio Miranda-Escalada

6 papers receiving 98 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Antonio Miranda-Escalada 102 66 8 6 6 6 121
Marco Basaldella 186 1.8× 121 1.8× 8 1.0× 3 0.5× 4 0.7× 14 218
Amy X. Lu 42 0.4× 73 1.1× 4 0.5× 9 1.5× 7 151
Asad Aali 128 1.3× 33 0.5× 2 0.3× 5 0.8× 3 0.5× 6 247
Rishabh Joshi 163 1.6× 38 0.6× 15 1.9× 3 0.5× 9 188
Shikhar Vashishth 205 2.0× 49 0.7× 7 0.9× 4 0.7× 13 227
Ziyang Xu 124 1.2× 31 0.5× 4 0.5× 1 0.2× 3 0.5× 11 239
Sky Faber 84 0.8× 31 0.5× 7 0.9× 11 1.8× 7 121
Shyamasree Saha 146 1.4× 86 1.3× 7 0.9× 6 1.0× 9 203
Madeleine van Zuylen 143 1.4× 31 0.5× 7 0.9× 3 0.5× 4 252
Mario Sänger 66 0.6× 57 0.9× 2 0.3× 1 0.2× 3 0.5× 10 80

Countries citing papers authored by Antonio Miranda-Escalada

Since Specialization
Citations

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

Fields of papers citing papers by Antonio Miranda-Escalada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Antonio Miranda-Escalada. 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 Antonio Miranda-Escalada. The network helps show where Antonio Miranda-Escalada may publish in the future.

Co-authorship network of co-authors of Antonio Miranda-Escalada

This figure shows the co-authorship network connecting the top 25 collaborators of Antonio Miranda-Escalada. A scholar is included among the top collaborators of Antonio Miranda-Escalada 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 Antonio Miranda-Escalada. Antonio Miranda-Escalada is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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