James Ford

70 papers receiving 1.9k citations

Peers

James Ford
Comparison fields: 5 of 143
  • Information Systems 426
  • Computational Mathematics 11
  • Neurology 275
  • Epidemiology 555
  • Computer Vision and Pattern Recognition 313
Replace Takahiro Ogawa with:
Takahiro Ogawa Japan
Suresh Subramaniam United States
Christopher J. Hughes United States
Vasileios Megalooikonomou Greece
Charence Wong United Kingdom
Afshin Shoeibi Iran
Tuo Zhang China
Xiaowei Xu China
Paul Dagum United States
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James Ford relative to Takahiro Ogawa Japan Takahiro Ogawa's profile →
Citations per field
00.5×4.2×
Takahiro Ogawa · 1×
Citations per year

Countries citing papers authored by James Ford

Since Specialization
Citations

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

Fields of papers citing papers by James Ford

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside James Ford, 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 James Ford Line = papers co-authored together James Ford links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 74 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006253
2 2013187
3 2011186
4 2004134
5 2014122
6 201380
7 200674
8 200670
9 200661
10 200661
11 200458
12 200054
13 201645
14 200444
15 200642
16 201539
17 200339
18 200636
19 200735
20 200833

About James Ford

James Ford is a scholar working on Computer Networks and Communications, Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems and Radiology, Nuclear Medicine and Imaging, having authored 74 papers that have together received 2.0k indexed citations. Recurring topics across this work include Traumatic Brain Injury Research (8 papers), Advanced Neuroimaging Techniques and Applications (7 papers), Medical Image Segmentation Techniques (6 papers), Automotive and Human Injury Biomechanics (6 papers), Recommender Systems and Techniques (6 papers), Image Retrieval and Classification Techniques (6 papers), Security in Wireless Sensor Networks (5 papers) and Peer-to-Peer Network Technologies (4 papers). The work is most often cited by research in Information Systems (426 citations), Computational Mathematics (11 citations), Neurology (275 citations), Epidemiology (555 citations) and Computer Vision and Pattern Recognition (313 citations). James Ford has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Fillia Makedon, Laura A. Flashman, Thomas W. McAllister, Weihong Wang, Richard M. Greenwald, Jonathan G. Beckwith, Sheng Zhang, Songbai Ji, Keith D. Paulsen and Justin D. Pearlman. Their work appears in journals such as Journal of Neurotrauma, NeuroImage, Annals of Biomedical Engineering, Statistical Methods in Medical Research and Computer applications in the biosciences.

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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