Se‐woon Choe

1.9k total citations
55 papers, 1.4k citations indexed

About

Se‐woon Choe is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Artificial Intelligence. According to data from OpenAlex, Se‐woon Choe has authored 55 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Radiology, Nuclear Medicine and Imaging, 18 papers in Biomedical Engineering and 16 papers in Artificial Intelligence. Recurrent topics in Se‐woon Choe's work include AI in cancer detection (15 papers), Radiomics and Machine Learning in Medical Imaging (13 papers) and Photoacoustic and Ultrasonic Imaging (9 papers). Se‐woon Choe is often cited by papers focused on AI in cancer detection (15 papers), Radiomics and Machine Learning in Medical Imaging (13 papers) and Photoacoustic and Ultrasonic Imaging (9 papers). Se‐woon Choe collaborates with scholars based in South Korea, United States and Ethiopia. Se‐woon Choe's co-authors include Gelan Ayana, Brian S. Sorg, S. Paul Oh, Kokeb Dese, Young Jae Lee, Hojong Choi, Yong Hwan Kim, Minseok Kim, Lei Wu and Huikai Xie and has published in prestigious journals such as Journal of Clinical Investigation, PLoS ONE and Circulation Research.

In The Last Decade

Se‐woon Choe

48 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Se‐woon Choe South Korea 20 380 330 317 306 223 55 1.4k
Atsushi Teramoto Japan 26 943 2.5× 172 0.5× 519 1.6× 198 0.6× 535 2.4× 153 2.5k
Ken Chang United States 23 1.4k 3.8× 443 1.3× 521 1.6× 253 0.8× 336 1.5× 51 2.2k
R. Jena United Kingdom 30 1.2k 3.2× 648 2.0× 116 0.4× 203 0.7× 613 2.7× 109 2.6k
Qiang Tian China 20 973 2.6× 483 1.5× 143 0.5× 118 0.4× 212 1.0× 47 1.4k
Xiaohua Qian China 24 619 1.6× 66 0.2× 344 1.1× 169 0.6× 190 0.9× 82 1.7k
Ke Zhao China 23 475 1.3× 212 0.6× 215 0.7× 125 0.4× 219 1.0× 125 1.8k
Alireza Mehrtash United States 16 1.2k 3.2× 85 0.3× 482 1.5× 328 1.1× 443 2.0× 32 1.8k
Albert Murtha Canada 26 622 1.6× 783 2.4× 100 0.3× 166 0.5× 828 3.7× 86 2.3k
Zijian Zhang China 23 388 1.0× 122 0.4× 84 0.3× 142 0.5× 326 1.5× 127 1.6k

Countries citing papers authored by Se‐woon Choe

Since Specialization
Citations

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

Fields of papers citing papers by Se‐woon Choe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Se‐woon Choe. 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 Se‐woon Choe. The network helps show where Se‐woon Choe may publish in the future.

Co-authorship network of co-authors of Se‐woon Choe

This figure shows the co-authorship network connecting the top 25 collaborators of Se‐woon Choe. A scholar is included among the top collaborators of Se‐woon Choe 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 Se‐woon Choe. Se‐woon Choe 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.
Ayana, Gelan, et al.. (2025). Vision Transformers for Low-Quality Histopathological Images: A Case Study on Squamous Cell Carcinoma Margin Classification. Diagnostics. 15(3). 260–260. 2 indexed citations
2.
Hwang, Min‐Jin, et al.. (2024). Drug release profile of phenytoin-loaded starch-based biomaterials incorporating hierarchical microparticles with photothermal effects. International Journal of Biological Macromolecules. 282(Pt 2). 136803–136803. 2 indexed citations
3.
Ayana, Gelan, et al.. (2024). Automated ECG Signals Analysis for Cardiac Abnormality Detection and Classification. Journal of Electrical Engineering and Technology. 19(5). 3355–3371. 5 indexed citations
4.
Ayana, Gelan & Se‐woon Choe. (2024). Vision Transformers-Based Transfer Learning for Breast Mass Classification From Multiple Diagnostic Modalities. Journal of Electrical Engineering and Technology. 19(5). 3391–3410. 8 indexed citations
5.
Park, Woohyun, Se‐woon Choe, & Minseok Kim. (2024). Microscale Flow Control and Droplet Generation Using Arduino-Based Pneumatically-Controlled Microfluidic Device. Biosensors. 14(10). 469–469. 2 indexed citations
6.
Ayana, Gelan, et al.. (2024). Superpixel-based Landmark Identification and Disease Diagnosis from Gastrointestinal Images. Journal of Electrical Engineering and Technology. 19(5). 3373–3389.
7.
Ayana, Gelan, et al.. (2024). Deep learning model meets community-based surveillance of acute flaccid paralysis. Infectious Disease Modelling. 10(1). 353–364.
8.
Kang, Ji‐Hoon, et al.. (2024). Synthesis, recognition properties and drug release behavior of diltiazem‐imprinted chitosan‐based biomaterials. Journal of Applied Polymer Science. 142(1).
9.
Ayana, Gelan, et al.. (2023). Vision-Transformer-Based Transfer Learning for Mammogram Classification. Diagnostics. 13(2). 178–178. 66 indexed citations
10.
Ayana, Gelan, et al.. (2023). Vision Transformers for Breast Cancer Human Epidermal Growth Factor Receptor 2 Expression Staging without Immunohistochemical Staining. American Journal Of Pathology. 194(3). 402–414. 8 indexed citations
11.
Ayana, Gelan, et al.. (2023). Domain and Histopathology Adaptations–Based Classification for Malignancy Grading System. American Journal Of Pathology. 193(12). 2080–2098. 7 indexed citations
12.
Ayana, Gelan, et al.. (2022). Progress of Near-Infrared-Based Medical Imaging and Cancer Cell Suppressors. Chemosensors. 10(11). 471–471. 7 indexed citations
13.
Choe, Se‐woon, et al.. (2022). Deep neural network incorporating domain and resolution transformations model for histopathological image classification. Computers & Electrical Engineering. 104. 108468–108468. 10 indexed citations
14.
Han, Chul Ju, Se‐woon Choe, Yong Hwan Kim, et al.. (2014). VEGF neutralization can prevent and normalize arteriovenous malformations in an animal model for hereditary hemorrhagic telangiectasia 2. Angiogenesis. 17(4). 823–830. 98 indexed citations
15.
Park, Sung O, Heather L. Wamsley, Kyung‐Mi Bae, et al.. (2013). Conditional Deletion of Jak2 Reveals an Essential Role in Hematopoiesis throughout Mouse Ontogeny: Implications for Jak2 Inhibition in Humans. PLoS ONE. 8(3). e59675–e59675. 49 indexed citations
16.
Kim, Yong Hwan, Se‐woon Choe, Yu Gyoung Tak, et al.. (2013). Enhanced Responses to Angiogenic Cues Underlie the Pathogenesis of Hereditary Hemorrhagic Telangiectasia 2. PLoS ONE. 8(5). e63138–e63138. 28 indexed citations
17.
Choe, Se‐woon, David S. Terman, Angela Rivers, et al.. (2013). Drug-loaded sickle cells programmed ex vivo for delayed hemolysis target hypoxic tumor microvessels and augment tumor drug delivery. Journal of Controlled Release. 171(2). 184–192. 19 indexed citations
18.
Sun, Jingjing, Shuguang Guo, Lei Wu, et al.. (2010). 3D In Vivo optical coherence tomography based on a low-voltage, large-scan-range 2D MEMS mirror. Optics Express. 18(12). 12065–12065. 127 indexed citations
19.
Park, Sung Ok, Mamta Wankhede, Young Jae Lee, et al.. (2009). Real-time imaging of de novo arteriovenous malformation in a mouse model of hereditary hemorrhagic telangiectasia. Journal of Clinical Investigation. 119(11). 3487–96. 233 indexed citations
20.
Choe, Se‐woon, et al.. (2009). Improvement of the PFCM(Possibilistic Fuzzy C-Means) Clustering Method. PubMed Central. 13(1). 177–185. 1 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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