David S. Channin

72 total papers · 1.7k total citations
53 papers, 1.2k citations indexed

About

David S. Channin is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Pulmonary and Respiratory Medicine. According to data from OpenAlex, David S. Channin has authored 53 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Radiology, Nuclear Medicine and Imaging, 17 papers in Artificial Intelligence and 15 papers in Pulmonary and Respiratory Medicine. Recurrent topics in David S. Channin's work include Radiology practices and education (17 papers), AI in cancer detection (12 papers) and Radiomics and Machine Learning in Medical Imaging (11 papers). David S. Channin is often cited by papers focused on Radiology practices and education (17 papers), AI in cancer detection (12 papers) and Radiomics and Machine Learning in Medical Imaging (11 papers). David S. Channin collaborates with scholars based in United States, Thailand and Philippines. David S. Channin's co-authors include Daniel L. Rubin, Eliot L. Siegel, Pattanasak Mongkolwat, Jing Song, Dorothy D. Dunlop, September Cahue, Leena Sharma, Charles E. Kahn, Jacob Furst and Daniela Raicu and has published in prestigious journals such as Radiology, American Journal of Roentgenology and Radiographics.

In The Last Decade

David S. Channin

53 papers receiving 1.1k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
David S. Channin 503 302 241 240 209 53 1.2k
Gwilym S. Lodwick 425 0.8× 232 0.8× 472 2.0× 136 0.6× 53 0.3× 59 1.2k
B. Wein 289 0.6× 404 1.3× 219 0.9× 242 1.0× 157 0.8× 90 1.5k
Mohammadhadi Bagheri 534 1.1× 144 0.5× 312 1.3× 178 0.7× 245 1.2× 66 1.5k
Shigao Huang 445 0.9× 301 1.0× 231 1.0× 67 0.3× 173 0.8× 46 1.2k
Satish E. Viswanath 833 1.7× 281 0.9× 516 2.1× 92 0.4× 80 0.4× 90 1.3k
Thomas Sanford 577 1.1× 414 1.4× 387 1.6× 153 0.6× 62 0.3× 63 1.4k
Masayuki Tsuneki 435 0.9× 505 1.7× 242 1.0× 233 1.0× 276 1.3× 51 1.5k
Suzie El‐Saden 226 0.4× 168 0.6× 354 1.5× 71 0.3× 133 0.6× 59 1.0k
Yuan Li 428 0.9× 160 0.5× 172 0.7× 131 0.5× 311 1.5× 118 1.4k
Thomas Clozel 458 0.9× 433 1.4× 167 0.7× 239 1.0× 330 1.6× 18 1.3k

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

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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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