John Kang

37 papers receiving 886 citations

Peers

John Kang
Comparison fields: 5 of 129
  • Health Informatics 34
  • Reproductive Medicine 81
  • Physiology 34
  • Cancer Research 96
  • Obstetrics and Gynecology 43
Replace Soichiro Yoshida with:
Soichiro Yoshida Japan
Jacob New United States
Axel Andrès Switzerland
Takahito Miyake Japan
Liat Appelbaum Israel
Guangjian Liu China
Gencay Hatiboglu Germany
Thomas S. Winokur United States
Hank Schmidt United States
Andrea Brunner Austria
John Kang relative to Soichiro Yoshida Japan Soichiro Yoshida's profile →
Citations per field
00.5×5.7×
Soichiro Yoshida · 1×
Citations per year

Countries citing papers authored by John Kang

Since Specialization
Citations

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

Fields of papers citing papers by John Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011166
2 2015152
3
Dysregulation of annexin I protein expression in high-grade prostatic intraepithelial neoplasia and prostate cancer.
2002107
4 199463
5 201851
6 202142
7 201237
8 201133
9 202230
10 201529
11 201424
12 198824
13 199920
14 199618
15 200416
16 200315
17 200113
18 202311
19 201510
20 20248

About John Kang

John Kang is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Radiation, Cell Biology and Biomedical Engineering, having authored 42 papers that have together received 912 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (8 papers), Advanced Radiotherapy Techniques (6 papers), Cellular Mechanics and Interactions (5 papers), AI in cancer detection (4 papers), Prostate Cancer Diagnosis and Treatment (4 papers), Force Microscopy Techniques and Applications (3 papers), Urinary Bladder and Prostate Research (3 papers) and Advances in Oncology and Radiotherapy (3 papers). The work is most often cited by research in Health Informatics (34 citations), Reproductive Medicine (81 citations), Physiology (34 citations), Cancer Research (96 citations) and Obstetrics and Gynecology (43 citations). John Kang has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Russell Schwartz, Sushil Beriwal, John C. Flíckinger, David K. Ornstein, Kwang‐Hyun Park, Uh‐Hyun Kim, Susan J. Maygarden, James L. Mohler, Benjamin F. Calvo and Laura S. Caskey. Their work appears in journals such as International Journal of Radiation Oncology*Biology*Physics, Biophysical Journal, Topics in Spinal Cord Injury Rehabilitation, Practical Radiation Oncology and Frontiers in 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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