John Kang

1.2k total citations
40 papers, 861 citations indexed

About

John Kang is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Radiation. According to data from OpenAlex, John Kang has authored 40 papers receiving a total of 861 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Radiology, Nuclear Medicine and Imaging, 9 papers in Pulmonary and Respiratory Medicine and 6 papers in Radiation. Recurrent topics in John Kang's work include Radiomics and Machine Learning in Medical Imaging (9 papers), Advanced Radiotherapy Techniques (6 papers) and Cellular Mechanics and Interactions (5 papers). John Kang is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (9 papers), Advanced Radiotherapy Techniques (6 papers) and Cellular Mechanics and Interactions (5 papers). John Kang collaborates with scholars based in United States, Canada and South Korea. John Kang's co-authors include Russell Schwartz, Sushil Beriwal, John C. Flíckinger, David K. Ornstein, Uh‐Hyun Kim, Susan J. Maygarden, Kwang‐Hyun Park, James L. Mohler, Benjamin F. Calvo and Laura S. Caskey and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

John Kang

37 papers receiving 845 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
John Kang United States 15 266 153 142 108 98 40 861
Giuseppe Fanetti Italy 18 126 0.5× 198 1.3× 161 1.1× 95 0.9× 118 1.2× 61 844
Julia Gallwas Germany 20 201 0.8× 120 0.8× 93 0.7× 87 0.8× 80 0.8× 77 1.2k
Hiroki Kiyohara Japan 23 235 0.9× 327 2.1× 142 1.0× 76 0.7× 133 1.4× 101 1.5k
Charles Roux France 23 386 1.5× 183 1.2× 143 1.0× 103 1.0× 43 0.4× 78 1.2k
N. Sellier France 17 127 0.5× 183 1.2× 143 1.0× 70 0.6× 35 0.4× 75 1.5k
Rathi Ramakrishnan United Kingdom 12 210 0.8× 173 1.1× 82 0.6× 180 1.7× 29 0.3× 29 797
Jacob New United States 12 393 1.5× 204 1.3× 279 2.0× 168 1.6× 87 0.9× 25 1.2k
Yu-Jie Huang Taiwan 21 118 0.4× 377 2.5× 220 1.5× 138 1.3× 36 0.4× 68 1.5k
Theodore Petsas Greece 21 242 0.9× 511 3.3× 135 1.0× 94 0.9× 48 0.5× 56 1.4k

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-authorship network of co-authors of John Kang

This figure shows the co-authorship network connecting the top 25 collaborators of John Kang. A scholar is included among the top collaborators of John Kang 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 John Kang. John Kang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Beidler, Peter G., et al.. (2025). Semiautomated Extraction of Research Topics and Trends From National Cancer Institute Funding in Radiological Sciences From 2000 to 2020. International Journal of Radiation Oncology*Biology*Physics. 122(2). 458–466.
2.
3.
Melançon, D, et al.. (2025). A Comparative Risk Analysis of Cone Beam Computed Tomography-based Daily Adaptive Radiation Therapy and Cone Beam Computed Tomography-based Radiation Therapy Alone. International Journal of Radiation Oncology*Biology*Physics. 122(4). 873–880.
4.
Kang, John, Kyle J. Lafata, Ellen Kim, et al.. (2024). Artificial intelligence across oncology specialties: current applications and emerging tools. SHILAP Revista de lepidopterología. 3(1). e000134–e000134. 6 indexed citations
5.
Chowdhry, Amit K., et al.. (2024). Finding Multiple Signals in the Noise: Handling Multiplicity in Clinical Trials. International Journal of Radiation Oncology*Biology*Physics. 119(3). 750–755. 3 indexed citations
6.
Meyer, Juergen, John Kang, D Melançon, et al.. (2023). Framework for Radiation Oncology Department-wide Evaluation and Implementation of Commercial Artificial Intelligence Autocontouring. Practical Radiation Oncology. 14(2). e150–e158. 7 indexed citations
7.
Wei, Bo, John Kang, Miho Kibukawa, et al.. (2022). Evaluation of the TruSight Oncology 500 Assay for Routine Clinical Testing of Tumor Mutational Burden and Clinical Utility for Predicting Response to Pembrolizumab. Journal of Molecular Diagnostics. 24(6). 600–608. 28 indexed citations
8.
Greer, Matthew D., et al.. (2022). Predicted Inferior Outcomes for Lung SBRT With Treatment Planning Systems That Fail Independent Phantom-Based Audits. International Journal of Radiation Oncology*Biology*Physics. 115(5). 1301–1308. 2 indexed citations
9.
Kang, John, et al.. (2021). Rhabdomyolysis in COVID-19 Patients: A Retrospective Observational Study. Cureus. 13(1). e12552–e12552. 42 indexed citations
10.
Kang, John, James T. Coates, Robert L. Strawderman, Barry S. Rosenstein, & Sarah L. Kerns. (2019). Radiogenomics models in precision radiotherapy: from mechanistic to machine learning. arXiv (Cornell University). 2 indexed citations
11.
Kang, John, et al.. (2017). Machine Learning to Predict Postradical Prostatectomy Pathology Outcomes in Intermediate Risk Prostate Cancer. International Journal of Radiation Oncology*Biology*Physics. 99(2). E245–E246. 1 indexed citations
12.
Minkoff, David, Beant S. Gill, John Kang, & Sushil Beriwal. (2015). Cervical cancer outcome prediction to high-dose rate brachytherapy using quantitative magnetic resonance imaging analysis of tumor response to external beam radiotherapy. Radiotherapy and Oncology. 115(1). 78–83. 28 indexed citations
13.
Kang, John, et al.. (2013). Modeling Mechanotransduction Signaling through Actin Filament Network Deformation Linked to Biochemical Response. Biophysical Journal. 104(2). 317a–318a. 1 indexed citations
14.
Kang, John, Kwang‐Hyun Park, Jwa-Jin Kim, et al.. (2012). The Role of CD38 in Fcγ Receptor (FcγR)-mediated Phagocytosis in Murine Macrophages. Journal of Biological Chemistry. 287(18). 14502–14514. 36 indexed citations
15.
Park, Kwang‐Hyun, Byoung‐Ju Kim, John Kang, et al.. (2011). Ca 2+ Signaling Tools Acquired from Prostasomes Are Required for Progesterone-Induced Sperm Motility. Science Signaling. 4(173). ra31–ra31. 156 indexed citations
16.
Kang, John, et al.. (2011). A coarse-Grained Monte Carlo Model of Cytoskeletal Actin Filament Alignment under Cyclic Stretch. Biophysical Journal. 100(3). 34a–34a. 1 indexed citations
17.
Kang, John, et al.. (2011). Response of an actin filament network model under cyclic stretching through a coarse grained Monte Carlo approach. Journal of Theoretical Biology. 274(1). 109–119. 33 indexed citations
18.
Kang, John, Susan J. Maygarden, James L. Mohler, & Raj S. Pruthi. (2004). Comparison of clinical and pathological features in African‐American and Caucasian patients with localized prostate cancer. British Journal of Urology. 93(9). 1207–1210. 16 indexed citations
19.
Ornstein, David K. & John Kang. (2001). How to improve prostate biopsy detection of prostate cancer. Current Urology Reports. 2(3). 218–223. 11 indexed citations
20.
Stürmann, Kai, et al.. (1999). Ultrasonographic guidance of transvenous pacemaker insertion in the emergency department: a report of three cases. Journal of Emergency Medicine. 17(3). 491–496. 15 indexed citations

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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2026