Brian E. Chapman

2.0k citations
60 papers · 1.5k · h-index 20

Impact in

Papers in

Brian E. Chapman

59 papers receiving 1.5k citations

Peers

Brian E. Chapman
Comparison fields: 5 of 141
  • Health Informatics 69
  • Radiology, Nuclear Medicine and Imaging 465
  • Internal Medicine 52
  • Health Information Management 74
  • Artificial Intelligence 462
Replace Shih-Cheng Huang with:
Shih-Cheng Huang United States
Anuj Pareek United States
Chris Chute United States
Jeremy Irvin United States
James Nichols United States
David A. Mong United States
Joseph A. Cruz Canada
Sheng Yu China
B. Wein Germany
Fei Shan China
Brian E. Chapman relative to Shih-Cheng Huang United States Shih-Cheng Huang's profile →
Citations per field
00.5×10×20×30×37.5×
Shih-Cheng Huang · 1×
Citations per year

Countries citing papers authored by Brian E. Chapman

Since Specialization
Citations

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

Fields of papers citing papers by Brian E. Chapman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Brian E. Chapman. 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 Brian E. Chapman. The network helps show where Brian E. Chapman may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018206
2 2017162
3 2003126
4 2011108
5 2011107
6 200188
7
Extending the NegEx lexicon for multiple languages.
201364
8 200455
9 199852
10 200346
11 200341
12 201038
13 201635
14 200433
15 201832
16 200529
17 200024
18 201921
19 200521
20 200420

About Brian E. Chapman

Brian E. Chapman is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Computer Vision and Pattern Recognition, Artificial Intelligence and Molecular Biology, having authored 60 papers that have together received 1.5k indexed citations. Recurring topics across this work include Advanced MRI Techniques and Applications (14 papers), Medical Image Segmentation Techniques (11 papers), Cerebrovascular and Carotid Artery Diseases (10 papers), Biomedical Text Mining and Ontologies (8 papers), MRI in cancer diagnosis (6 papers), Radiology practices and education (6 papers), Topic Modeling (5 papers) and Lung Cancer Diagnosis and Treatment (4 papers). The work is most often cited by research in Health Informatics (69 citations), Radiology, Nuclear Medicine and Imaging (465 citations), Internal Medicine (52 citations), Health Information Management (74 citations) and Artificial Intelligence (462 citations). Brian E. Chapman has collaborated with scholars based in United States, Sweden and Australia. Frequent co-authors include Wendy W. Chapman, Dennis L. Parker, Matthew P. Lungren, Timothy J. Amrhein, Curtis P. Langlotz, N Moradzadeh, Sean Lee, Hyunseok P. Kang, Peter J. Haug and Andrew L. Alexander. Their work appears in journals such as Journal of Magnetic Resonance Imaging, Journal of Biomedical Informatics, Academic Radiology, Magnetic Resonance in Medicine and Radiology.

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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