Katelyn Smith

487 citations
20 papers · 293 · h-index 8

Impact in

  • Oncology top 10%
    • Pancreatic and Hepatic Oncology Research
    • Cancer Immunotherapy and Biomarkers
    • Artificial Intelligence in Healthcare and Education

Papers in

    • Pancreatic and Hepatic Oncology Research 11
    • Cancer Immunotherapy and Biomarkers 1

Katelyn Smith

16 papers receiving 290 citations

Peers

Katelyn Smith
Comparison fields: 5 of 27
  • Oncology 217
  • Health Informatics 6
  • Surgery 50
  • Pulmonary and Respiratory Medicine 26
  • Hepatology 6
Replace Jung Won Chun with:
Jung Won Chun South Korea
Maria Passhak Israel
Sandipkumar H. Patel United States
Denise Bianchi Italy
Kenta Nakahara Japan
Rachel E. Simpson United States
Yasushi Oda Japan
Laure Monard France
Ken Yamashita Japan
Joost M.J. Geesing Netherlands
Katelyn Smith relative to Jung Won Chun South Korea Jung Won Chun's profile →
Citations per field
00.5×1.5×
Jung Won Chun · 1×
Citations per year

Countries citing papers authored by Katelyn Smith

Since Specialization
Citations

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

Fields of papers citing papers by Katelyn Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 2022132
2 202340
3 202039
4 202115
5 202314
6 202313
7 20208
8 20228
9 20257
10 20235
11 20243
12 20253
13 20212
14 20252
15 20231
16 20261
17 20230
18 20230
19 20260
20 20260

About Katelyn Smith

Katelyn Smith is a scholar working on Oncology, Hepatology, Surgery, Pulmonary and Respiratory Medicine and Epidemiology, having authored 20 papers that have together received 293 indexed citations. Recurring topics across this work include Pancreatic and Hepatic Oncology Research (11 papers), Cholangiocarcinoma and Gallbladder Cancer Studies (3 papers), Gallbladder and Bile Duct Disorders (3 papers), Neuroendocrine Tumor Research Advances (3 papers), AI in cancer detection (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Telomeres, Telomerase, and Senescence (1 paper) and Cancer Immunotherapy and Biomarkers (1 paper). The work is most often cited by research in Oncology (217 citations), Health Informatics (6 citations), Surgery (50 citations), Pulmonary and Respiratory Medicine (26 citations) and Hepatology (6 citations). Katelyn Smith has collaborated with scholars based in United States, Denmark and Italy. Frequent co-authors include Amer H. Zureikat, Mazen S. Zenati, Alessandro Paniccia, James A. Brown, Herbert J. Zeh, Melissa Ellen Hogg, Kenneth K.W. Lee, Amr I. Al Abbas, Richard L. Simmons and Sowmya Narayanan. Their work appears in journals such as Gastrointestinal Endoscopy, Gastroenterology, Modern Pathology, Annals of Surgical Oncology and Journal of Surgical Oncology.

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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