Darrell N. Smith

26 papers receiving 1.5k citations

Peers

Darrell N. Smith
Comparison fields: 5 of 85
  • Pathology and Forensic Medicine 769
  • Cancer Research 540
  • Dermatology 300
  • Radiology, Nuclear Medicine and Imaging 514
  • Critical Care and Intensive Care Medicine 76
Replace Fatih Aydoğan with:
Fatih Aydoğan Türkiye
Derek Muradali Canada
Jung‐Gi Im South Korea
Paul E. Wallner United States
Gia A. DeAngelis United States
Hyun Ju Lee South Korea
M. Zinninger United States
Kee‐Min Yeow Taiwan
Hyo Soon Lim South Korea
Figen Demirkazık Türkiye
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Citations per year

Countries citing papers authored by Darrell N. Smith

Since Specialization
Citations

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

Fields of papers citing papers by Darrell N. Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Darrell N. Smith. 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 Darrell N. Smith. The network helps show where Darrell N. Smith may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001493
2 2000220
3 1990183
4 1998111
5 199788
6 200182
7 199761
8 200557
9 199738
10 200033
11 200026
12 199924
13 200418
14 199718
15 200018
16 199816
17 200215
18 199910
19 19989
20 20079

About Darrell N. Smith

Darrell N. Smith is a scholar working on Pathology and Forensic Medicine, Dermatology, Cancer Research, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 28 papers that have together received 1.6k indexed citations. Recurring topics across this work include Breast Lesions and Carcinomas (16 papers), Breast Cancer Treatment Studies (9 papers), Cancer and Skin Lesions (9 papers), AI in cancer detection (4 papers), Advanced MRI Techniques and Applications (4 papers), Salivary Gland Tumors Diagnosis and Treatment (3 papers), MRI in cancer diagnosis (3 papers) and Medical Imaging Techniques and Applications (2 papers). The work is most often cited by research in Pathology and Forensic Medicine (769 citations), Cancer Research (540 citations), Dermatology (300 citations), Radiology, Nuclear Medicine and Imaging (514 citations) and Critical Care and Intensive Care Medicine (76 citations). Darrell N. Smith has collaborated with scholars based in United States and Japan. Frequent co-authors include Jack E. Meyer, Christine M. Denison, Susan C. Lester, Daniel E. Singer, Michael J. Fine, Pamela J. DiPiro, Ferenc A. Jólesz, Nathan McDannold, Peter Huber and Samuel Singer. Their work appears in journals such as Radiology, The Breast Journal, American Journal of Roentgenology, Cancer and Radiologic Clinics of North America.

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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