Sung Hun Kim

6.1k total citations · 1 hit paper
259 papers, 4.4k citations indexed

About

Sung Hun Kim is a scholar working on Radiology, Nuclear Medicine and Imaging, Pathology and Forensic Medicine and Artificial Intelligence. According to data from OpenAlex, Sung Hun Kim has authored 259 papers receiving a total of 4.4k indexed citations (citations by other indexed papers that have themselves been cited), including 113 papers in Radiology, Nuclear Medicine and Imaging, 78 papers in Pathology and Forensic Medicine and 44 papers in Artificial Intelligence. Recurrent topics in Sung Hun Kim's work include MRI in cancer diagnosis (71 papers), Breast Lesions and Carcinomas (71 papers) and Radiomics and Machine Learning in Medical Imaging (64 papers). Sung Hun Kim is often cited by papers focused on MRI in cancer diagnosis (71 papers), Breast Lesions and Carcinomas (71 papers) and Radiomics and Machine Learning in Medical Imaging (64 papers). Sung Hun Kim collaborates with scholars based in South Korea, United States and Hong Kong. Sung Hun Kim's co-authors include Bong Joo Kang, Byung Joo Song, Bong Joo Kang, Seung Hee Jeong, Hyeon Woo Yim, Jae Jeong Choi, Yeong Yi An, Hyeon Sook Kim, Ahwon Lee and Chang Suk Park and has published in prestigious journals such as SHILAP Revista de lepidopterología, ACS Nano and Applied Physics Letters.

In The Last Decade

Sung Hun Kim

242 papers receiving 4.3k citations

Hit Papers

A Survey on Mixture of Experts in Large Language Models 2025 2026 2025 5 10 15 20
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A Survey on Mixture of Experts in Large Language Models
    2025 20 citations Sung Hun Kim et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sung Hun Kim South Korea 36 2.0k 860 739 724 562 259 4.4k
Ruey‐Feng Chang Taiwan 39 2.7k 1.4× 531 0.6× 233 0.3× 2.8k 3.9× 579 1.0× 189 4.9k
Eric K. Oermann United States 32 1.1k 0.5× 421 0.5× 258 0.3× 775 1.1× 1.1k 1.9× 122 4.6k
Jun Xia China 25 2.0k 1.0× 151 0.2× 267 0.4× 1.2k 1.7× 464 0.8× 124 4.0k
Ming Y. Lu United States 33 1.4k 0.7× 108 0.1× 430 0.6× 1.5k 2.1× 235 0.4× 76 4.7k
Jakob Nikolas Kather Germany 44 3.3k 1.7× 318 0.4× 1.1k 1.5× 3.3k 4.6× 733 1.3× 214 7.7k
Eunjung Lee South Korea 38 929 0.5× 197 0.2× 176 0.2× 289 0.4× 244 0.4× 222 5.2k
Feng‐Sheng Wang Taiwan 55 592 0.3× 266 0.3× 958 1.3× 396 0.5× 265 0.5× 278 9.2k
Tetsuya Higuchi Japan 30 896 0.5× 121 0.1× 520 0.7× 343 0.5× 614 1.1× 181 3.8k
Liang Jin China 27 638 0.3× 76 0.1× 228 0.3× 512 0.7× 505 0.9× 154 3.0k
Wei Qian China 37 2.1k 1.1× 127 0.1× 181 0.2× 1.2k 1.7× 1.4k 2.4× 234 4.9k

Countries citing papers authored by Sung Hun Kim

Since Specialization
Citations

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

Fields of papers citing papers by Sung Hun Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sung Hun Kim. 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 Sung Hun Kim. The network helps show where Sung Hun Kim may publish in the future.

Co-authorship network of co-authors of Sung Hun Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Sung Hun Kim. A scholar is included among the top collaborators of Sung Hun Kim 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 Sung Hun Kim. Sung Hun Kim 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
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Zhou, Peilin, X. R. Zhou, Yueqi Xie, et al.. (2025). When Large Vision Language Models Meet Multimodal Sequential Recommendation: An Empirical Study. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 275–292.
3.
Zhang, Peiyan, Xi Zhang, Chaozhuo Li, et al.. (2024). TransGNN: Harnessing the Collaborative Power of Transformers and Graph Neural Networks for Recommender Systems. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 1285–1295. 20 indexed citations
4.
Zhou, Peilin, et al.. (2024). Is Contrastive Learning Necessary? A Study of Data Augmentation vs Contrastive Learning in Sequential Recommendation. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 3854–3863. 7 indexed citations
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Park, Chang Suk, et al.. (2023). Diagnostic Usefulness of Diffusion-Weighted MRI for Axillary Lymph Node Evaluation in Patients with Breast Cancer. Diagnostics. 13(3). 513–513. 6 indexed citations
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Kim, Sung Hun, et al.. (2021). Upgrade of gamma electron vertex imaging system for high-performance range verification in pencil beam scanning proton therapy. Nuclear Engineering and Technology. 54(3). 1016–1023. 5 indexed citations
10.
Yoo, Tae-Kyung, Bong Joo Kang, Sung Hun Kim, et al.. (2020). Axillary lymph node dissection is not obligatory in breast cancer patients with biopsy-proven axillary lymph node metastasis. Breast Cancer Research and Treatment. 181(2). 403–409. 12 indexed citations
11.
Kim, Sung Hun, Jae Kwan Jun, Yun‐Woo Chang, et al.. (2019). Interpretive Performance and Inter-Observer Agreement on Digital Mammography Test Sets. Korean Journal of Radiology. 20(2). 218–218. 14 indexed citations
12.
Lee, Youn Joo, et al.. (2019). Triple-negative breast cancer: Pretreatment magnetic resonance imaging features and clinicopathological factors associated with recurrence. Magnetic Resonance Imaging. 66. 36–41. 10 indexed citations
13.
Kim, Sung Hun, Bong Joo Kang, Ji Hye Lee, et al.. (2012). Diffusion-weighted imaging and FDG PET/CT: predicting the prognoses with apparent diffusion coefficient values and maximum standardized uptake values in patients with invasive ductal carcinoma. World Journal of Surgical Oncology. 10(1). 126–126. 58 indexed citations
14.
Yeo, Min-Ju, et al.. (2011). Japanese Encephalitis in Korea, 2010: Case Reports and Epidemiology. Journal of the Korean Neurological Association. 29(4). 335–338. 2 indexed citations
15.
Kim, Sung Hun, et al.. (2009). Clinical Study of the Floating-Sinking Pulse Quantification Analysis on Ages, Left/Right, and Palpation Positions. Journal of Physiology & Pathology in Korean Medicine. 23(5). 1193–1198. 6 indexed citations
16.
Lee, Jungju, Sang Kun Lee, Dong Wook Kim, et al.. (2009). Ictal spect using an attachable automated injector: clinical usefulness in the prediction of ictal onset zone. Acta Radiologica. 50(10). 1160–1168. 3 indexed citations
17.
Lee, Seung Hwan, et al.. (2008). Brain Areas Involved in Grapheme-Phoneme Conversion of Hangeul: A fMRI Study. Dementia and Neurocognitive Disorders. 7(2). 47–51. 1 indexed citations
18.
Bae, Jong Seok, et al.. (2006). Subclinical Diabetic Neuropathy with Normal Conventional Nerve Conduction Study. Journal of the Korean Neurological Association. 24(6). 557–563. 1 indexed citations
19.
Kim, Sung Hun, et al.. (2005). The Clinical Analysis of 25 Cases of Bezoars. Journal of the Korean Surgical Society. 68(5). 407–413. 5 indexed citations
20.
Ko, Eun Young, Sung Hun Kim, Kyu‐Sun Lee, et al.. (2004). The Clinical Characteristics of Anemia in Type 2 Diabetic Patients Without Overt Nephropathy. Diabetes & Metabolism Journal. 28(5). 425–431. 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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