David W. Brammer

725 total citations
13 papers, 374 citations indexed

About

David W. Brammer is a scholar working on Surgery, Radiology, Nuclear Medicine and Imaging and Epidemiology. According to data from OpenAlex, David W. Brammer has authored 13 papers receiving a total of 374 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Surgery, 5 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Epidemiology. Recurrent topics in David W. Brammer's work include Lipoproteins and Cardiovascular Health (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and MRI in cancer diagnosis (2 papers). David W. Brammer is often cited by papers focused on Lipoproteins and Cardiovascular Health (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and MRI in cancer diagnosis (2 papers). David W. Brammer collaborates with scholars based in United States, United Kingdom and Israel. David W. Brammer's co-authors include Michael J. Ryan, Mark D. Rekhter, Vijaykumar M. Baragi, Sally R. Frenkel, Richard R. Renkiewicz, Blake J. Roessler, Luping Qiu, Robert E. Sigler, Steven B. Abramson and Joan A. Keiser and has published in prestigious journals such as PLoS ONE, Circulation Research and Arteriosclerosis Thrombosis and Vascular Biology.

In The Last Decade

David W. Brammer

13 papers receiving 362 citations

Peers

David W. Brammer
Viktoryia Kazlouskaya United States
David W. Brammer
Citations per year, relative to David W. Brammer David W. Brammer (= 1×) peers Viktoryia Kazlouskaya

Countries citing papers authored by David W. Brammer

Since Specialization
Citations

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

Fields of papers citing papers by David W. Brammer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David W. Brammer

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

All Works

13 of 13 papers shown
1.
Ng, Chaan S., Wei Wei, James A. Bankson, et al.. (2015). Dependence of DCE-MRI biomarker values on analysis algorithm. PLoS ONE. 10(7). e0130168–e0130168. 21 indexed citations
2.
Ng, Chaan S., John C. Waterton, Vikas Kundra, et al.. (2012). Reproducibility and Comparison of DCE-MRI and DCE-CT Perfusion Parameters in a Rat Tumor Model. Technology in Cancer Research & Treatment. 11(3). 279–288. 19 indexed citations
3.
Tian, Mei, Kazuma Ogawa, Richard E. Wendt, et al.. (2011). Whole-Body Biodistribution Kinetics, Metabolism, and Radiation Dosimetry Estimates of 18F-PEG6-IPQA in Nonhuman Primates. Journal of Nuclear Medicine. 52(6). 934–941. 8 indexed citations
4.
Sanchez, Brian, et al.. (2008). Use of a portable thermal imaging unit as a rapid, quantitative method of evaluating inflammation and experimental arthritis. Journal of Pharmacological and Toxicological Methods. 57(3). 169–175. 37 indexed citations
5.
Gibson, Glenn, Cynthia L. Courtney, Michael D. Huband, et al.. (2007). Development of a mouse model of induced Staphylococcus aureus infective endocarditis.. PubMed. 57(6). 563–9. 22 indexed citations
6.
Brammer, David W., et al.. (2007). Harderian gland adenectomy: a method to eliminate confounding radio-opacity in the assessment of rat brain metabolism by 18F-fluoro-2-deoxy-D-glucose positron emission tomography.. PubMed. 46(5). 42–5. 7 indexed citations
7.
Rekhter, Mark D., David W. Brammer, Hussein Hallak, et al.. (2000). Hypercholesterolemia Causes Mechanical Weakening of Rabbit Atheroma. Circulation Research. 86(1). 101–108. 61 indexed citations
8.
Ryan, Michael J., et al.. (1998). Influence of lipoprotein(a) plasma concentration on neointimal growth in a monkey model of vascular injury. Atherosclerosis. 139(1). 137–145. 2 indexed citations
9.
Brammer, David W., et al.. (1998). Spontaneous hyperthyroidism in an aged male and femaleMacaca mulatta. Journal of Medical Primatology. 27(6). 273–277. 11 indexed citations
10.
Rekhter, Mark D., David W. Brammer, Jong Seung Kim, et al.. (1998). Animal Model That Mimics Atherosclerotic Plaque Rupture. Circulation Research. 83(7). 705–713. 64 indexed citations
11.
Baragi, Vijaykumar M., Richard R. Renkiewicz, Luping Qiu, et al.. (1997). Transplantation of adenovirally transduced allogeneic chondrocytes into articular cartilage defects in vivo. Osteoarthritis and Cartilage. 5(4). 275–282. 101 indexed citations
12.
Ryan, Michael J., et al.. (1997). Localization of Lipoprotein(a) in a Monkey Model of Rapid Neointimal Growth. Arteriosclerosis Thrombosis and Vascular Biology. 17(1). 181–187. 13 indexed citations
13.
Brammer, David W., et al.. (1993). Pseudomonas aeruginosa infection in a Chinchilla lanigera. Laboratory Animals. 27(2). 131–133. 8 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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