John Kilbourne

578 total citations
10 papers, 386 citations indexed

About

John Kilbourne is a scholar working on Molecular Biology, Health Information Management and Artificial Intelligence. According to data from OpenAlex, John Kilbourne has authored 10 papers receiving a total of 386 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 5 papers in Health Information Management and 3 papers in Artificial Intelligence. Recurrent topics in John Kilbourne's work include Biomedical Text Mining and Ontologies (8 papers), Electronic Health Records Systems (5 papers) and Semantic Web and Ontologies (3 papers). John Kilbourne is often cited by papers focused on Biomedical Text Mining and Ontologies (8 papers), Electronic Health Records Systems (5 papers) and Semantic Web and Ontologies (3 papers). John Kilbourne collaborates with scholars based in United States and Australia. John Kilbourne's co-authors include Kelly Zeng, Stuart J. Nelson, Tammy Powell, Olivier Bodenreider, Nhan Do, Omar Bouhaddou, M J Lincoln, Frank A. Parrish, Joshua C. Mandel and Michael T. Rupp and has published in prestigious journals such as Journal of the American Medical Informatics Association, International Journal of Data Mining and Bioinformatics and PubMed.

In The Last Decade

John Kilbourne

9 papers receiving 372 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
John Kilbourne United States	6	193	124	101	58	46	10	386
Kelly Zeng United States	7	193 1.0×	130 1.0×	84 0.8×	61 1.1×	42 0.9×	12	383
Tammy Powell United States	4	192 1.0×	124 1.0×	71 0.7×	55 0.9×	46 1.0×	7	390
Shane P. Stenner United States	8	237 1.2×	209 1.7×	133 1.3×	27 0.5×	53 1.2×	11	563
Tanya Podchiyska United States	7	129 0.7×	169 1.4×	106 1.0×	38 0.7×	61 1.3×	10	389
Robert Eriksson Denmark	11	138 0.7×	142 1.1×	65 0.6×	29 0.5×	60 1.3×	22	581
Joseph M. Plasek United States	13	108 0.6×	127 1.0×	58 0.6×	31 0.5×	81 1.8×	42	544
Erica A. Voss United States	11	88 0.5×	76 0.6×	60 0.6×	38 0.7×	43 0.9×	27	500
Fleur Mougin France	13	270 1.4×	240 1.9×	46 0.5×	65 1.1×	84 1.8×	52	484
Haijun Zhai United States	11	120 0.6×	201 1.6×	82 0.8×	13 0.2×	33 0.7×	19	464
Henk Harkema United States	12	339 1.8×	401 3.2×	76 0.8×	28 0.5×	26 0.6×	22	646

Countries citing papers authored by John Kilbourne

Since Specialization

Citations

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

Fields of papers citing papers by John Kilbourne

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John Kilbourne

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

All Works

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10 of 10 papers shown

1.

Rupp, Michael T., et al.. (2015). Evaluating the implementation of RxNorm in ambulatory electronic prescriptions. Journal of the American Medical Informatics Association. 23(e1). e99–e107. 8 indexed citations

2.

Nelson, Stuart J., et al.. (2011). Normalized names for clinical drugs: RxNorm at 6 years. Journal of the American Medical Informatics Association. 18(4). 441–448. 297 indexed citations

3.

Nelson, Stuart J., Kelly Zeng, & John Kilbourne. (2011). Building a standards-based and collaborative e-prescribing tool: MyRxPad. International Journal of Data Mining and Bioinformatics. 5(3). 252–252. 5 indexed citations

4.

Nelson, Stuart J., Kelly Zeng, & John Kilbourne. (2009). Building a Standards-Based and Collaborative E-Prescribing Tool MyRxPad. 61. 210–215. 2 indexed citations

5.

Riben, Michael, et al.. (2008). Aligning tissue banking data models for caBIG interoperability.. PubMed. 1109–1109. 4 indexed citations

6.

Zeng, Kelly, Olivier Bodenreider, John Kilbourne, & Stuart J. Nelson. (2007). RxNav: Towards an Integrated View on Drug Information. 2400. 7 indexed citations

7.

Bouhaddou, Omar, Frank A. Parrish, Nhan Do, et al.. (2007). Exchange of Computable Patient Data between the Department of Veterans Affairs (VA) and the Department of Defense (DoD): Terminology Mediation Strategy. Journal of the American Medical Informatics Association. 15(2). 174–183. 36 indexed citations

8.

Bouhaddou, Omar, et al.. (2007). Use of RxNorm to exchange codified drug allergy information between Department of Veterans Affairs (VA) and Department of Defense (DoD).. PubMed. 781–5. 9 indexed citations

9.

Zeng, Kelly, Olivier Bodenreider, John Kilbourne, & Stuart J. Nelson. (2006). RxNav: a web service for standard drug information.. PubMed. 1156–1156. 18 indexed citations

10.

Kilbourne, John, et al.. (2003). Unicode, UTF-8, ASCII, and SNOMED CT.. PubMed. 892–892.

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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