Joan Kapusnik-Uner

32 total papers · 516 total citations
21 papers, 251 citations indexed

About

Joan Kapusnik-Uner is a scholar working on Molecular Biology, Geriatrics and Gerontology and Artificial Intelligence. According to data from OpenAlex, Joan Kapusnik-Uner has authored 21 papers receiving a total of 251 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 7 papers in Geriatrics and Gerontology and 7 papers in Artificial Intelligence. Recurrent topics in Joan Kapusnik-Uner's work include Biomedical Text Mining and Ontologies (8 papers), Pharmaceutical Practices and Patient Outcomes (7 papers) and Semantic Web and Ontologies (7 papers). Joan Kapusnik-Uner is often cited by papers focused on Biomedical Text Mining and Ontologies (8 papers), Pharmaceutical Practices and Patient Outcomes (7 papers) and Semantic Web and Ontologies (7 papers). Joan Kapusnik-Uner collaborates with scholars based in United States. Joan Kapusnik-Uner's co-authors include Olivier Bodenreider, Candy Tsourounis, Kin Wah Fung, John J. Schmitz, Carol A. Broverman, Thắng Nguyễn, Yehoshua Perl, Meena Sachdeva, Merle A. Sande and Y. W. Francis Lam and has published in prestigious journals such as Annals of the New York Academy of Sciences, Clinical Pharmacology & Therapeutics and Journal of the American Medical Informatics Association.

In The Last Decade

Joan Kapusnik-Uner

21 papers receiving 237 citations

Author Peers

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

Author Last Decade Papers Cites
Joan Kapusnik-Uner 69 54 44 39 38 21 251
Julie Birdie Wahlang 69 1.0× 52 1.0× 20 0.5× 11 0.3× 4 0.1× 16 303
Matthew J. Seamon 21 0.3× 113 2.1× 6 0.1× 32 0.8× 17 0.4× 18 324
Ze Yu 23 0.3× 12 0.2× 34 0.8× 14 0.4× 5 0.1× 30 285
Deema Jaber 12 0.2× 75 1.4× 13 0.3× 15 0.4× 8 0.2× 40 252
Marco Egbring 22 0.3× 46 0.9× 6 0.1× 16 0.4× 9 0.2× 16 256
Mark A. Parkulo 21 0.3× 16 0.3× 10 0.2× 12 0.3× 7 0.2× 17 307
Gerri Kaufman 28 0.4× 67 1.2× 3 0.1× 22 0.6× 15 0.4× 38 325
Juan D. Chaparro 47 0.7× 20 0.4× 33 0.8× 94 2.4× 3 0.1× 19 288
Irina Iaru 30 0.4× 52 1.0× 6 0.1× 5 0.1× 7 0.2× 22 253
Amy Wilson 33 0.5× 33 0.6× 5 0.1× 9 0.2× 16 0.4× 21 254

Countries citing papers authored by Joan Kapusnik-Uner

Since Specialization
Citations

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

Fields of papers citing papers by Joan Kapusnik-Uner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joan Kapusnik-Uner. 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 Joan Kapusnik-Uner. The network helps show where Joan Kapusnik-Uner may publish in the future.

Co-authorship network of co-authors of Joan Kapusnik-Uner

This figure shows the co-authorship network connecting the top 25 collaborators of Joan Kapusnik-Uner. A scholar is included among the top collaborators of Joan Kapusnik-Uner 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 Joan Kapusnik-Uner. Joan Kapusnik-Uner 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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