David Birtwell

461 total citations
9 papers, 99 citations indexed

About

David Birtwell is a scholar working on Genetics, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, David Birtwell has authored 9 papers receiving a total of 99 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Genetics, 4 papers in Molecular Biology and 3 papers in Artificial Intelligence. Recurrent topics in David Birtwell's work include Biomedical Text Mining and Ontologies (3 papers), Semantic Web and Ontologies (3 papers) and Genomics and Rare Diseases (2 papers). David Birtwell is often cited by papers focused on Biomedical Text Mining and Ontologies (3 papers), Semantic Web and Ontologies (3 papers) and Genomics and Rare Diseases (2 papers). David Birtwell collaborates with scholars based in United States. David Birtwell's co-authors include Christian J. Stoeckert, Daniel J. Rader, Jay Giri, Mathias Brochhausen, Scott M. Damrauer, Anna Maria Masci, Jie Zheng, Aeron Small, Marie Guerraty and John H. Holmes and has published in prestigious journals such as Kidney International, Cancer Epidemiology Biomarkers & Prevention and Journal of Biomedical Informatics.

In The Last Decade

David Birtwell

9 papers receiving 95 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
David Birtwell United States	6	37	30	25	17	16	9	99
Monika Ahuja India	4	28 0.8×	11 0.4×	7 0.3×	8 0.5×	17 1.1×	8	130
Matthieu Wargny France	9	23 0.6×	23 0.8×	24 1.0×	42 2.5×	8 0.5×	22	153
Fabrício S. P. Kury United States	6	76 2.1×	53 1.8×	40 1.6×	7 0.4×	10 0.6×	12	164
Jason Ross United States	4	46 1.2×	37 1.2×	20 0.8×	11 0.6×	12 0.8×	7	141
Hang Yan China	7	27 0.7×	13 0.4×	7 0.3×	27 1.6×	13 0.8×	25	131
Gabrielle Bertier France	6	36 1.0×	10 0.3×	75 3.0×	5 0.3×	41 2.6×	14	169
Maria Pikoula United Kingdom	5	18 0.5×	23 0.8×	5 0.2×	4 0.2×	3 0.2×	7	130
Philip Schroeder United States	6	19 0.5×	12 0.4×	45 1.8×	21 1.2×	8 0.5×	10	99
Haley Hunter-Zinck United States	4	49 1.3×	15 0.5×	79 3.2×	10 0.6×	6 0.4×	4	171
P H M Peeters Netherlands	5	25 0.7×	19 0.6×	11 0.4×	18 1.1×	33 2.1×	6	129

Countries citing papers authored by David Birtwell

Since Specialization

Citations

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

Fields of papers citing papers by David Birtwell

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Birtwell

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

All Works

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9 of 9 papers shown

1.

Miller, Mark A., et al.. (2020). A novel tool for standardizing clinical data in a semantically rich model. Journal of Biomedical Informatics. 112. 100086–100086. 7 indexed citations

2.

Falcone, Mary, Chongliang Luo, Yong Chen, et al.. (2020). Risk of Persistent Opioid Use following Major Surgery in Matched Samples of Patients with and without Cancer. Cancer Epidemiology Biomarkers & Prevention. 29(11). 2126–2133. 7 indexed citations

3.

Bajaj, Archna, Chengxiang Qiu, Aeron Small, et al.. (2020). Phenome-wide association analysis suggests the APOL1 linked disease spectrum primarily drives kidney-specific pathways. Kidney International. 97(5). 1032–1041. 17 indexed citations

4.

Birtwell, David, E. Georg Luebeck, & Carlo C. Maley. (2020). The evolution of metapopulation dynamics and the number of stem cells in intestinal crypts and other tissue structures in multicellular bodies. Evolutionary Applications. 13(7). 1771–1783. 5 indexed citations

5.

Birtwell, David, et al.. (2019). Carnival: A Graph-Based Data Integration and Query Tool to Support Patient Cohort Generation for Clinical Research. Studies in health technology and informatics. 264. 35–39. 4 indexed citations

6.

Stoeckert, Christian J., et al.. (2018). Transforming and Unifying Research with Biomedical Ontologies: The Penn TURBO Project.. 1 indexed citations

7.

Levin, Michael G., Rachel L. Kember, Renae Judy, et al.. (2018). Genomic Risk Stratification Predicts All-Cause Mortality After Cardiac Catheterization. Circulation Genomic and Precision Medicine. 11(11). e002352–e002352. 17 indexed citations

8.

Small, Aeron, David Birtwell, Marie Guerraty, et al.. (2017). Text mining applied to electronic cardiovascular procedure reports to identify patients with trileaflet aortic stenosis and coronary artery disease. Journal of Biomedical Informatics. 72. 77–84. 22 indexed citations

9.

Brochhausen, Mathias, et al.. (2016). OBIB-a novel ontology for biobanking. Journal of Biomedical Semantics. 7(1). 23–23. 19 indexed citations

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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