David S. Channin

1.7k citations
53 papers · 1.2k indexed · h-index 18
Topics
Radiology practices and education (17 papers)AI in cancer detection (12 papers)Radiomics and Machine Learning in Medical Imaging (11 papers)

In The Last Decade

David S. Channin

53 papers receiving 1.1k citations

Peers

David S. Channin
Comparison fields: 5 of 104
  • Radiology, Nuclear Medicine and Imaging 504
  • Artificial Intelligence 303
  • Pulmonary and Respiratory Medicine 241
  • Surgery 241
  • Molecular Biology 210
Replace W. Dean Bidgood with:
W. Dean Bidgood United States
Gwilym S. Lodwick United States
David Clunie United States
Mona G. Flores United States
Steven M. Montner United States
Ali Abbasian Ardakani Iran
Georgios C. Manikis Greece
Shigao Huang China
Christiane M. Hakim United States
Mohammad Amin Morid United States
David S. Channin relative to W. Dean Bidgood United States W. Dean Bidgood's profile →
Citations per field
00.5×2.7×
W. Dean Bidgood · 1×
Citations per year

Countries citing papers authored by David S. Channin

Since Specialization
Citations

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

Fields of papers citing papers by David S. Channin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David S. Channin. 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 David S. Channin. The network helps show where David S. Channin may publish in the future.

Co-authorship network of co-authors of David S. Channin

This figure shows the co-authorship network connecting the top 25 collaborators of David S. Channin. A scholar is included among the top collaborators of David S. Channin 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 David S. Channin. David S. Channin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 13
2 23
3 24
4 85
5 170
6
Medical Imaging on the Semantic Web: Annotation and Image Markup.
55
7 17
8 10
9 9
10 63
11 20
12 58
13 22
14 5
15 2
16 3
17 1
18 6
19 3
20 1

About David S. Channin

David S. Channin is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Pulmonary and Respiratory Medicine, having authored 53 papers that have together received 1.2k indexed citations. Recurring topics across this work include Radiology practices and education (17 papers), AI in cancer detection (12 papers) and Radiomics and Machine Learning in Medical Imaging (11 papers). The work is most often cited by research in Health Informatics (45 citations), Radiology, Nuclear Medicine and Imaging (504 citations) and Health Information Management (86 citations). David S. Channin has collaborated with scholars based in United States, Thailand and Philippines. Frequent co-authors include Daniel L. Rubin, Eliot L. Siegel, Pattanasak Mongkolwat, Dorothy D. Dunlop, Leena Sharma, September Cahue, Jing Song, Charles E. Kahn, Curtis P. Langlotz and Daniela Raicu. Their work appears in journals such as Radiology, American Journal of Roentgenology and Radiographics.

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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