Kyung‐Hyun Do

6.1k total citations · 1 hit paper
146 papers, 3.5k citations indexed

About

Kyung‐Hyun Do is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Epidemiology. According to data from OpenAlex, Kyung‐Hyun Do has authored 146 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 84 papers in Pulmonary and Respiratory Medicine, 52 papers in Radiology, Nuclear Medicine and Imaging and 22 papers in Epidemiology. Recurrent topics in Kyung‐Hyun Do's work include Lung Cancer Diagnosis and Treatment (34 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (28 papers) and Radiomics and Machine Learning in Medical Imaging (26 papers). Kyung‐Hyun Do is often cited by papers focused on Lung Cancer Diagnosis and Treatment (34 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (28 papers) and Radiomics and Machine Learning in Medical Imaging (26 papers). Kyung‐Hyun Do collaborates with scholars based in South Korea, United States and Ethiopia. Kyung‐Hyun Do's co-authors include Joon Beom Seo, Jooae Choe, Hyun Jung Koo, Sang Min Lee, Sang‐Ho Choi, Heungsup Sung, Soyeoun Lim, Jin Woo Song, Se Jin Jang and Eun Jin Chae and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and The Science of The Total Environment.

In The Last Decade

Kyung‐Hyun Do

133 papers receiving 3.4k citations

Hit Papers

Radiographic and CT Featu... 2018 2026 2020 2023 2018 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kyung‐Hyun Do South Korea 29 1.6k 1.3k 742 537 478 146 3.5k
Bruno Hochhegger Brazil 32 1.7k 1.0× 768 0.6× 765 1.0× 484 0.9× 524 1.1× 330 3.4k
Robert M. Steiner United States 28 1.2k 0.8× 529 0.4× 806 1.1× 702 1.3× 426 0.9× 123 2.9k
Jonathan H. Chung United States 31 2.9k 1.8× 1.2k 1.0× 742 1.0× 459 0.9× 720 1.5× 170 4.6k
Yeon‐Mok Oh South Korea 40 3.8k 2.3× 360 0.3× 859 1.2× 616 1.1× 528 1.1× 358 5.9k
Paolo Ricci Italy 32 784 0.5× 970 0.8× 827 1.1× 852 1.6× 636 1.3× 166 3.7k
Amita Sharma United States 27 1.3k 0.8× 573 0.5× 475 0.6× 550 1.0× 101 0.2× 124 2.9k
Kyung Soo Chung South Korea 36 1.7k 1.1× 274 0.2× 1.1k 1.4× 797 1.5× 468 1.0× 203 4.6k
Man Pyo Chung South Korea 41 3.7k 2.3× 448 0.4× 1.4k 1.9× 945 1.8× 904 1.9× 230 5.5k
Doreen Addrizzo‐Harris United States 20 1.5k 0.9× 256 0.2× 413 0.6× 637 1.2× 246 0.5× 52 2.9k
Yi Dong China 33 741 0.5× 1.1k 0.8× 1.1k 1.4× 1.3k 2.4× 247 0.5× 231 3.9k

Countries citing papers authored by Kyung‐Hyun Do

Since Specialization
Citations

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

Fields of papers citing papers by Kyung‐Hyun Do

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kyung‐Hyun Do. 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 Kyung‐Hyun Do. The network helps show where Kyung‐Hyun Do may publish in the future.

Co-authorship network of co-authors of Kyung‐Hyun Do

This figure shows the co-authorship network connecting the top 25 collaborators of Kyung‐Hyun Do. A scholar is included among the top collaborators of Kyung‐Hyun Do 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 Kyung‐Hyun Do. Kyung‐Hyun Do 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.
Ahn, Yura, et al.. (2025). Prevalence and Risk Factors for Pathologic N2 Disease in Resected Lung Cancers Assessed as N0 or N1 Disease on Preoperative Imaging. American Journal of Roentgenology. 224(5). e2432486–e2432486.
2.
Ahn, Yura, Sang Min Lee, Jooae Choe, et al.. (2025). Prognostic Implications of the Volume Doubling Time of the Solid Component in Lung Adenocarcinomas Manifesting as Part-Solid Lesions on Chest CT. American Journal of Roentgenology. 224(4). e2432470–e2432470.
3.
Kim, Seong Min, et al.. (2025). Radiation dose reduction and image quality enhancement for patients unable to elevate their arms in chest CT: A comparative study. European Journal of Radiology. 188. 112120–112120.
4.
Lee, Han Na, Kyung‐Hyun Do, Eun Young Kim, et al.. (2024). Comparative Analysis of CT Findings and Clinical Outcomes in Adult Patients With Disseminated and Localized Pulmonary Nocardiosis. Journal of Korean Medical Science. 39(11). e107–e107. 6 indexed citations
5.
Ahn, Yura, Seong-Soo Choi, Jaewon Choe, et al.. (2024). CT-guided pretreatment biopsy diagnosis in patients with thymic epithelial tumours: diagnostic accuracy and risk of seeding. Clinical Radiology. 79(4). 263–271. 2 indexed citations
6.
Ahn, Hee‐Sung, So‐Yeon Lee, Mi‐Jin Kang, et al.. (2024). Polyhexamethylene guanidine aerosol causes irreversible changes in blood proteins that associated with the severity of lung injury. Journal of Hazardous Materials. 478. 135359–135359. 4 indexed citations
7.
Park, Sohee, Sang Min Lee, Wooil Kim, et al.. (2021). Computer-aided Detection of Subsolid Nodules at Chest CT: Improved Performance with Deep Learning–based CT Section Thickness Reduction. Radiology. 299(1). 211–219. 17 indexed citations
8.
Lee, Sang‐Oh, Kyung‐Wook Jo, Sehoon Choi, et al.. (2020). Infections in Lung Transplant Recipients during and after Prophylaxis. Infection and Chemotherapy. 52(4). 600–600. 8 indexed citations
9.
Cho, Eun‐Jung, et al.. (2020). Serum Krebs von den Lungen-6 level predicts disease progression in interstitial lung disease. PLoS ONE. 15(12). e0244114–e0244114. 18 indexed citations
10.
Park, Sohee, Sang Min Lee, Kyung‐Hyun Do, et al.. (2019). Deep Learning Algorithm for Reducing CT Slice Thickness: Effect on Reproducibility of Radiomic Features in Lung Cancer. Korean Journal of Radiology. 20(10). 1431–1431. 57 indexed citations
11.
Jo, Kyung‐Wook, Sang‐Bum Hong, Dong Kwan Kim, et al.. (2019). Long-Term Outcomes of Adult Lung Transplantation Recipients: A Single-Center Experience in South Korea. Tuberculosis & respiratory diseases. 82(4). 348–348. 6 indexed citations
12.
Lee, Han Na, et al.. (2019). Human Bocavirus Infection in Adults: Clinical Features and Radiological Findings. Korean Journal of Radiology. 20(7). 1226–1226. 12 indexed citations
13.
Choi, Sehoon, Seung-Il Park, Geun Dong Lee, et al.. (2018). The First Living-Donor Lobar Lung Transplantation in Korea: a Case Report. Journal of Korean Medical Science. 33(43). e282–e282. 4 indexed citations
14.
Lee, Han Na, Sang Min Lee, Jooae Choe, et al.. (2017). Diagnostic performance of CT-guided percutaneous transthoracic core needle biopsy using low tube voltage (100 kVp): comparison with conventional tube voltage (120 kVp). Acta Radiologica. 59(4). 425–433. 18 indexed citations
16.
Koo, Hyun Jung, et al.. (2016). Lung Cancer in Combined Pulmonary Fibrosis and Emphysema: A Systematic Review and Meta-Analysis. PLoS ONE. 11(9). e0161437–e0161437. 54 indexed citations
17.
Jeong, Woo Kyoung, Jung Hwan Baek, Seung Eun Jung, et al.. (2016). Imaging Guidelines for Enhancing Justifications for Radiologic Studies. Journal of Korean Medical Science. 31(Suppl 1). S38–S38. 7 indexed citations
18.
Choi, Seong‐Ho, Sang‐Bum Hong, Tark Kim, et al.. (2014). Clinical and molecular characterization of rhinoviruses A, B, and C in adult patients with pneumonia. Journal of Clinical Virology. 63. 70–75. 20 indexed citations
19.
Do, Kyung‐Hyun. (2011). The health effects of low-dose radiation exposure. Journal of Korean Medical Association. 54(12). 1253–1253. 12 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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