John Kang

37 papers receiving 845 citations

Peers

John Kang
Comparison fields: 5 of 131
  • Health Informatics 37
  • Reproductive Medicine 84
  • Physiology 33
  • Cancer Research 108
  • Radiation 59
Replace Hui Yuan with:
Hui Yuan China
Soichiro Yoshida Japan
Jacob New United States
Guangjian Liu China
Philipp Baumeister Germany
Christian D. Fankhauser Switzerland
Harrison X. Bai United States
Štefan Porubský Germany
Jia Sun United States
John Kang relative to Hui Yuan China Hui Yuan's profile →
Citations per field
00.5×6.6×
Hui Yuan · 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 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011156
2 2015142
3
Dysregulation of annexin I protein expression in high-grade prostatic intraepithelial neoplasia and prostate cancer.
2002105
4 199458
5 201845
6 202142
7 201236
8 201133
9 202228
10 201528
11 201424
12 198824
13 200416
14 199616
15 199915
16 200313
17 200111
18 202311
19 201510
20 20237

About John Kang

John Kang is a scholar working on Health Informatics, Radiation, Radiology, Nuclear Medicine and Imaging, Urology and Cell Biology, having authored 40 papers that have together received 861 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (9 papers), Advanced Radiotherapy Techniques (6 papers), Cellular Mechanics and Interactions (5 papers), Advances in Oncology and Radiotherapy (4 papers), Prostate Cancer Treatment and Research (4 papers), AI in cancer detection (4 papers), Prostate Cancer Diagnosis and Treatment (4 papers) and Urinary Bladder and Prostate Research (3 papers). The work is most often cited by research in Health Informatics (37 citations), Reproductive Medicine (84 citations), Physiology (33 citations), Cancer Research (108 citations) and Radiation (59 citations). John Kang has collaborated with scholars based in United States, South Korea and Canada. Frequent co-authors include Russell Schwartz, Sushil Beriwal, John C. Flíckinger, David K. Ornstein, Kwang‐Hyun Park, Susan J. Maygarden, James L. Mohler, Uh‐Hyun Kim, Laura S. Caskey and Benjamin F. Calvo. Their work appears in journals such as International Journal of Radiation Oncology*Biology*Physics, Biophysical Journal, Scientific Reports, Acta Ophthalmologica and JCO Clinical Cancer Informatics.

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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