Yeun‐Yoon Kim

1.2k total citations
39 papers, 743 citations indexed

About

Yeun‐Yoon Kim is a scholar working on Hepatology, Epidemiology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Yeun‐Yoon Kim has authored 39 papers receiving a total of 743 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Hepatology, 21 papers in Epidemiology and 13 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Yeun‐Yoon Kim's work include Hepatocellular Carcinoma Treatment and Prognosis (21 papers), Liver Disease Diagnosis and Treatment (20 papers) and Liver Disease and Transplantation (8 papers). Yeun‐Yoon Kim is often cited by papers focused on Hepatocellular Carcinoma Treatment and Prognosis (21 papers), Liver Disease Diagnosis and Treatment (20 papers) and Liver Disease and Transplantation (8 papers). Yeun‐Yoon Kim collaborates with scholars based in South Korea, United States and Saudi Arabia. Yeun‐Yoon Kim's co-authors include Myeong‐Jin Kim, Chansik An, Jin‐Young Choi, Yun Ho Roh, Eun Hwa Kim, Sung‐Won Kim, Jaeseung Shin, Sunyoung Lee, Mi‐Suk Park and Woo Kyoung Jeong and has published in prestigious journals such as SHILAP Revista de lepidopterología, Radiology and Journal of Hepatology.

In The Last Decade

Yeun‐Yoon Kim

38 papers receiving 737 citations

Peers

Yeun‐Yoon Kim
Toru Arano Japan
Masashi Kono Japan
Wan-Yee Lau Hong Kong
Robert Damm Germany
Diana Feier Romania
Tianfu Wen China
Antonia D’Errico Grigioni Italy
Cai‐Fang Ni China
Zhengqing Lei China
Riccardo Inchingolo Italy
Toru Arano Japan
Yeun‐Yoon Kim
Citations per year, relative to Yeun‐Yoon Kim Yeun‐Yoon Kim (= 1×) peers Toru Arano

Countries citing papers authored by Yeun‐Yoon Kim

Since Specialization
Citations

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

Fields of papers citing papers by Yeun‐Yoon Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yeun‐Yoon 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 Yeun‐Yoon Kim. The network helps show where Yeun‐Yoon Kim may publish in the future.

Co-authorship network of co-authors of Yeun‐Yoon Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Yeun‐Yoon Kim. A scholar is included among the top collaborators of Yeun‐Yoon 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 Yeun‐Yoon Kim. Yeun‐Yoon 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
1.
2.
Yoon, Jeong Hee, In Rae Cho, Won Chang, et al.. (2024). Survey of Experts’ Opinions on the Diagnosis and Management of Pancreatic Cystic Neoplasms. Korean Journal of Radiology. 25(12). 1047–1047. 1 indexed citations
3.
Song, Byeong Geun, Tae Wook Kang, Dong Hyun Sinn, et al.. (2024). Ultrasonographic findings of metabolic dysfunction-associated fatty liver disease: A comparative study with non-alcoholic fatty liver disease and clinical characteristics. Clinical Imaging. 108. 110097–110097. 2 indexed citations
4.
Kim, Yeun‐Yoon & Jin‐Young Choi. (2023). CT/MRI Liver Imaging Reporting and Data System (LI-RADS): Standardization, Evidence, and Future Direction. SHILAP Revista de lepidopterología. 84(1). 15–15. 1 indexed citations
5.
Choi, Seo‐Youn, Ji Hye Min, Jung Hoon Kim, et al.. (2023). Interobserver Variability and Diagnostic Performance in Predicting Malignancy of Pancreatic Intraductal Papillary Mucinous Neoplasm with MRI. Radiology. 308(1). e222463–e222463. 9 indexed citations
6.
Lee, Sunyoung, Yeun‐Yoon Kim, Jaeseung Shin, et al.. (2023). Percentages of Hepatocellular Carcinoma in LI-RADS Categories with CT and MRI: A Systematic Review and Meta-Analysis. Radiology. 307(1). e220646–e220646. 23 indexed citations
7.
Lee, Sunyoung, Yeun‐Yoon Kim, Jaeseung Shin, et al.. (2023). Liver Imaging Reporting and Data System version 2018 category 5 for diagnosing hepatocellular carcinoma: an updated meta-analysis. European Radiology. 34(3). 1502–1514. 7 indexed citations
8.
Kim, Yeun‐Yoon, Ji Hye Min, Jeong Ah Hwang, et al.. (2022). Second-line Sonazoid-enhanced ultrasonography for Liver Imaging Reporting and Data System category 3 and 4 on gadoxetate-enhanced magnetic resonance imaging. ULTRASONOGRAPHY. 41(3). 519–529. 6 indexed citations
9.
Kim, Yeun‐Yoon, Sunyoung Lee, Jaeseung Shin, et al.. (2022). Diagnostic performance of CT versus MRI Liver Imaging Reporting and Data System category 5 for hepatocellular carcinoma: a systematic review and meta-analysis of comparative studies. European Radiology. 32(10). 6723–6729. 9 indexed citations
10.
Kim, Yeun‐Yoon, Young Kon Kim, Ji Hye Min, et al.. (2021). Intraindividual Comparison of Hepatocellular Carcinoma Washout between MRIs with Hepatobiliary and Extracellular Contrast Agents. Korean Journal of Radiology. 22(5). 725–725. 4 indexed citations
11.
Hwang, Jeong Ah, Woo Kyoung Jeong, Ji Hye Min, et al.. (2021). Sonazoid-enhanced ultrasonography: comparison with CT/MRI Liver Imaging Reporting and Data System in patients with suspected hepatocellular carcinoma. ULTRASONOGRAPHY. 40(4). 486–498. 27 indexed citations
12.
Kim, Yeun‐Yoon, Myeong‐Jin Kim, Sung‐Min Gho, & Nieun Seo. (2020). Comparison of multiplexed sensitivity encoding and single-shot echo-planar imaging for diffusion-weighted imaging of the liver. European Journal of Radiology. 132. 109292–109292. 16 indexed citations
13.
Kim, Chang Gon, Chan Kim, Sang Eun Yoon, et al.. (2020). Hyperprogressive disease during PD-1 blockade in patients with advanced hepatocellular carcinoma. Journal of Hepatology. 74(2). 350–359. 136 indexed citations
14.
Lee, Sunyoung, Yeun‐Yoon Kim, Jaeseung Shin, et al.. (2020). CT and MRI Liver Imaging Reporting and Data System Version 2018 for Hepatocellular Carcinoma: A Systematic Review With Meta-Analysis. Journal of the American College of Radiology. 17(10). 1199–1206. 48 indexed citations
15.
Kim, Yeun‐Yoon, Tae Wook Kang, Dong Ik, et al.. (2020). Gadoxetic acid-enhanced MRI for differentiating hepatic sclerosing hemangioma from malignant tumor. European Journal of Radiology. 135. 109474–109474. 8 indexed citations
16.
Kim, Yeun‐Yoon, Jeeyun Lee, Woo Kyoung Jeong, et al.. (2020). Prognostic significance of sarcopenia in microsatellite-stable gastric cancer patients treated with programmed death-1 inhibitors. Gastric Cancer. 24(2). 457–466. 44 indexed citations
17.
Kim, Beom Kyung, Jun Yong Park, Do Young Kim, et al.. (2019). Risk assessment of hepatocellular carcinoma development for indeterminate hepatic nodules in patients with chronic hepatitis B. Clinical and Molecular Hepatology. 25(4). 390–399. 20 indexed citations
18.
Kim, Yeun‐Yoon, et al.. (2019). Gadoxetic acid-enhanced magnetic resonance imaging: Hepatocellular carcinoma and mimickers. Clinical and Molecular Hepatology. 25(3). 223–233. 35 indexed citations
19.
Kim, Yeun‐Yoon, Jin‐Young Choi, Claude B. Sirlin, Chansik An, & Myeong‐Jin Kim. (2018). Pitfalls and problems to be solved in the diagnostic CT/MRI Liver Imaging Reporting and Data System (LI-RADS). European Radiology. 29(3). 1124–1132. 27 indexed citations
20.
Kim, Yeun‐Yoon, Hyun Joo Shin, Myung‐Joon Kim, & Mi‐Jung Lee. (2016). Comparison of effective radiation doses from X-ray, CT, and PET/CT in pediatric patients with neuroblastoma using a dose monitoring program. Diagnostic and Interventional Radiology. 22(4). 390–394. 29 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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