William D. Dunn
Impact in
- Genetics top 10%
- Glioma Diagnosis and Treatment
- Human-Animal Interaction Studies
-
- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
- Medical Imaging Techniques and Applications
Papers in
-
- Radiomics and Machine Learning in Medical Imaging 5
- MRI in cancer diagnosis 2
- Advanced Neuroimaging Techniques and Applications 1
- Genetics 6
- Glioma Diagnosis and Treatment 6
- Co-authors
- David A. Gutman (9 shared papers)Hugo J.W.L. Aerts (4 shared papers)Chad A. Holder (3 shared papers)Patrick Großmann (2 shared papers)Lee Cooper (6 shared papers)Brian M. Alexander (2 shared papers)Todd M. Preuss (1 shared paper)Marc Kent (1 shared paper)
- Journals
- Scientific Reports (2 papers)Neuroradiology (1 paper)Acta Neuropathologica Communications (1 paper)Journal of Neuroscience (1 paper)Neoplasia (1 paper)
- Partner nations
- United StatesSwitzerlandFrance
In The Last Decade
William D. Dunn
16 papers receiving 438 citations
Peers
Comparison fields: 5 of 96
- Genetics 143
- Radiology, Nuclear Medicine and Imaging 210
- Health Informatics 8
- Neurology 38
- Biophysics 20
Countries citing papers authored by William D. Dunn
This map shows the geographic impact of William D. Dunn'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 William D. Dunn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William D. Dunn more than expected).
Fields of papers citing papers by William D. Dunn
This network shows the impact of papers produced by William D. Dunn. 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 William D. Dunn. The network helps show where William D. Dunn may publish in the future.
Co-authors
The 25 scholars most cited alongside William D. Dunn, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 73 | |
| 2 | 2015 | 68 | |
| 3 | 2019 | 68 | |
| 4 | 2016 | 57 | |
| 5 | 2015 | 42 | |
| 6 | 2008 | 26 | |
| 7 | 2016 | 24 | |
| 8 | 2016 | 21 | |
| 9 | 2017 | 19 | |
| 10 | 2015 | 18 | |
| 11 | 2016 | 15 | |
| 12 | 2014 | 8 | |
| 13 | 2015 | 5 | |
| 14 | 1990 | 3 | |
| 15 | 2016 | 1 | |
| 16 | 2015 | 1 |
About William D. Dunn
William D. Dunn is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics, Molecular Biology, Pulmonary and Respiratory Medicine and Computer Vision and Pattern Recognition, having authored 16 papers that have together received 449 indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (6 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Cell Image Analysis Techniques (2 papers), Ferroptosis and cancer prognosis (2 papers), MRI in cancer diagnosis (2 papers), Advanced Neuroimaging Techniques and Applications (1 paper), MicroRNA in disease regulation (1 paper) and Nanoplatforms for cancer theranostics (1 paper). The work is most often cited by research in Genetics (143 citations), Radiology, Nuclear Medicine and Imaging (210 citations), Health Informatics (8 citations), Neurology (38 citations) and Biophysics (20 citations). William D. Dunn has collaborated with scholars based in United States, Switzerland and France. Frequent co-authors include David A. Gutman, Hugo J.W.L. Aerts, Chad A. Holder, Patrick Großmann, Lee Cooper, Brian M. Alexander, Todd M. Preuss, Marc Kent, Daniel J. Brat and Jeroen B. Smaers. Their work appears in journals such as Scientific Reports, Neuroradiology, Acta Neuropathologica Communications, Journal of Neuroscience and Neoplasia.
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.