William G. Howe
- Radiology, Nuclear Medicine and Imaging top 10%
- Statistics and Probability top 5%
- Statistics, Probability and Uncertainty top 5%
- Management Science and Operations Research top 10%
- Biomedical Engineering
- Co-authors
- Markus SchwaigerNassir NavabSibylle ZieglerRené M. BotnarRalph A. BundschuhStephan G. NekollaDarko ZikicAxel Martínez-Möller
- Topics
- Medical Imaging Techniques and Applications (3 papers)Radiomics and Machine Learning in Medical Imaging (2 papers)Advanced Statistical Methods and Models (2 papers)
- Cited by
- Statistics and ProbabilityStatistics, Probability and UncertaintyRadiology, Nuclear Medicine and Imaging
- Partner nations
- United StatesIsraelGermany
In The Last Decade
William G. Howe
10 papers receiving 319 citations
Peers
Comparison fields: 5 of 76
- Radiology, Nuclear Medicine and Imaging 139
- Statistics and Probability 99
- Statistics, Probability and Uncertainty 55
- Management Science and Operations Research 53
- Biomedical Engineering 48
Countries citing papers authored by William G. Howe
This map shows the geographic impact of William G. Howe'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 G. Howe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William G. Howe more than expected).
Fields of papers citing papers by William G. Howe
This network shows the impact of papers produced by William G. Howe. 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 G. Howe. The network helps show where William G. Howe may publish in the future.
Co-authorship network of co-authors of William G. Howe
This figure shows the co-authorship network connecting the top 25 collaborators of William G. Howe. A scholar is included among the top collaborators of William G. Howe 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 William G. Howe. William G. Howe is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 26 | |
| 2 | 5 | |
| 3 | 107 | |
| 4 | 9 | |
| 5 | 3 | |
| 6 | 23 | |
| 7 | 73 | |
| 8 | 2 | |
| 9 | 83 | |
| 10 | 17 |
About William G. Howe
William G. Howe is a scholar working on Statistics and Probability, Radiology, Nuclear Medicine and Imaging and Radiation, having authored 10 papers that have together received 348 indexed citations. Recurring topics across this work include Medical Imaging Techniques and Applications (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Advanced Statistical Methods and Models (2 papers). The work is most often cited by research in Statistics and Probability (99 citations), Statistics, Probability and Uncertainty (55 citations) and Radiology, Nuclear Medicine and Imaging (139 citations). William G. Howe has collaborated with scholars based in United States, Israel and Germany. Frequent co-authors include Markus Schwaiger, Nassir Navab, Sibylle Ziegler, René M. Botnar, Ralph A. Bundschuh, Stephan G. Nekolla, Darko Zikic, Axel Martínez-Möller, Fred W. Billmeyer and W. R. J. Brown. Their work appears in journals such as Journal of the American Statistical Association, Technometrics and Operations Research.
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.