James Ford

86 papers receiving 2.3k citations

Peers

James Ford
Comparison fields: 5 of 139
  • Computational Mathematics 15
  • Information Systems 513
  • Neurology 246
  • Epidemiology 545
  • Computer Vision and Pattern Recognition 394
Replace Takahiro Ogawa with:
Takahiro Ogawa Japan
Christopher J. Hughes United States
Vasileios Megalooikonomou Greece
Tuo Zhang China
Paul Dagum United States
Suresh Subramaniam United States
Hyung-Jeong Yang South Korea
Manhua Liu China
Maurizio Filippone United Kingdom
Adi Alhudhaif Saudi Arabia
James Ford relative to Takahiro Ogawa Japan Takahiro Ogawa's profile →
Citations per field
00.5×4.4×
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 92 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006285
2 2013198
3 2011195
4 2004158
5 2014131
6 201384
7 200684
8 200680
9 200669
10 200667
11 200065
12 200464
13 200362
14 200651
15 201651
16 200450
17 200343
18 201542
19 200742
20 200742

About James Ford

James Ford is a scholar working on Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition, Information Systems and Radiology, Nuclear Medicine and Imaging, having authored 92 papers that have together received 2.4k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (8 papers), Traumatic Brain Injury Research (8 papers), Image Retrieval and Classification Techniques (8 papers), Advanced Neuroimaging Techniques and Applications (7 papers), Energy Efficient Wireless Sensor Networks (6 papers), Security in Wireless Sensor Networks (6 papers), Recommender Systems and Techniques (6 papers) and Underwater Vehicles and Communication Systems (5 papers). The work is most often cited by research in Computational Mathematics (15 citations), Information Systems (513 citations), Neurology (246 citations), Epidemiology (545 citations) and Computer Vision and Pattern Recognition (394 citations). James Ford has collaborated with scholars based in United States, United Kingdom and Greece. Frequent co-authors include Fillia Makedon, Laura A. Flashman, Thomas W. McAllister, Weihong Wang, Jonathan G. Beckwith, Sheng Zhang, Richard M. Greenwald, Andrew J. Saykin, Songbai Ji and Li Shen. Their work appears in journals such as Journal of Neurotrauma, NeuroImage, Statistical Methods in Medical Research, Annals of Biomedical Engineering and Lecture notes in computer science.

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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