Stephen Bowden

754 citations
42 papers · 543 · h-index 11

Impact in

Papers in

Stephen Bowden

38 papers receiving 533 citations

Peers

Stephen Bowden
Comparison fields: 5 of 87
  • Genetics 287
  • Radiology, Nuclear Medicine and Imaging 126
  • Neurology 79
  • Management of Technology and Innovation 28
  • Health Informatics 5
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Youngkyun Kim South Korea
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John Y. Lee United States
Yoshiko Okita Japan
Eva María Corrales-García Spain
Silvia Chiesa Italy
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Ricardo Díez Valle Spain
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Citations per field
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Citations per year

Countries citing papers authored by Stephen Bowden

Since Specialization
Citations

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

Fields of papers citing papers by Stephen Bowden

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Stephen Bowden, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Stephen Bowden Line = papers co-authored together Stephen Bowden links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016124
2 201784
3 201453
4 201652
5 201741
6 202236
7 200633
8 201816
9 201915
10 201813
11
The Impact of Question Response Structure on Recipient Attitude: A Field Study in Knowledge Sharing.
200510
12 20228
13 20248
14 20117
15 20216
16 20204
17 20214
18 20203
19 20033
20 20222

About Stephen Bowden

Stephen Bowden is a scholar working on Genetics, Radiology, Nuclear Medicine and Imaging, Surgery, Epidemiology and Neurology, having authored 42 papers that have together received 543 indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (14 papers), Meningioma and schwannoma management (7 papers), Pituitary Gland Disorders and Treatments (4 papers), MRI in cancer diagnosis (4 papers), Surgical Simulation and Training (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Disaster Management and Resilience (3 papers) and Cardiac, Anesthesia and Surgical Outcomes (3 papers). The work is most often cited by research in Genetics (287 citations), Radiology, Nuclear Medicine and Imaging (126 citations), Neurology (79 citations), Management of Technology and Innovation (28 citations) and Health Informatics (5 citations). Stephen Bowden has collaborated with scholars based in United States, New Zealand and United Kingdom. Frequent co-authors include Jeffrey N. Bruce, Peter Canoll, Adam M. Sonabend, Jorge Samanamud, Timothy H. Ung, Sameer A. Sheth, Michael B. Sisti, Guy M. McKhann, Daniel Chow and Hani Malone. Their work appears in journals such as Journal of Management & Organization, World Neurosurgery, Neurosurgery, Journal of neurosurgery and American Journal of Neuroradiology.

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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