Sang-Suk Han

510 total citations
11 papers, 384 citations indexed

About

Sang-Suk Han is a scholar working on Radiology, Nuclear Medicine and Imaging, Surgery and Oncology. According to data from OpenAlex, Sang-Suk Han has authored 11 papers receiving a total of 384 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Radiology, Nuclear Medicine and Imaging, 2 papers in Surgery and 2 papers in Oncology. Recurrent topics in Sang-Suk Han's work include Pancreatic and Hepatic Oncology Research (2 papers), MRI in cancer diagnosis (2 papers) and Hepatocellular Carcinoma Treatment and Prognosis (2 papers). Sang-Suk Han is often cited by papers focused on Pancreatic and Hepatic Oncology Research (2 papers), MRI in cancer diagnosis (2 papers) and Hepatocellular Carcinoma Treatment and Prognosis (2 papers). Sang-Suk Han collaborates with scholars based in South Korea. Sang-Suk Han's co-authors include Cheol Min Park, Pyo Nyun Kim, Hyunchul Rhim, Yun Hwan Kim, Won-Jae Lee, Hyo Keun Lim, Jeong Min Lee, Kwon‐Ha Yoon, June-Sik Cho and Seung Hoon Kim and has published in prestigious journals such as Radiographics, Journal of Vascular and Interventional Radiology and Journal of Ultrasound in Medicine.

In The Last Decade

Sang-Suk Han

11 papers receiving 371 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sang-Suk Han South Korea 6 211 132 121 88 82 11 384
Byung Hee Koh South Korea 7 219 1.0× 112 0.8× 121 1.0× 94 1.1× 61 0.7× 13 391
Zhimei Huang China 11 174 0.8× 88 0.7× 80 0.7× 96 1.1× 46 0.6× 33 327
Susan Pellicano Italy 4 271 1.3× 77 0.6× 110 0.9× 103 1.2× 82 1.0× 16 442
Carmine Coppola Italy 16 466 2.2× 140 1.1× 359 3.0× 65 0.7× 65 0.8× 32 617
Yun Ku Cho South Korea 10 347 1.6× 162 1.2× 226 1.9× 74 0.8× 29 0.4× 21 436
Bettina Saar Germany 13 135 0.6× 153 1.2× 68 0.6× 154 1.8× 180 2.2× 24 552
Eugenia Peri Italy 9 418 2.0× 159 1.2× 317 2.6× 90 1.0× 70 0.9× 10 548
Yoshiyasu Kisaka Japan 13 445 2.1× 146 1.1× 382 3.2× 40 0.5× 63 0.8× 24 552
N Furumoto United States 11 253 1.2× 268 2.0× 81 0.7× 193 2.2× 64 0.8× 17 512
H. Rieß Germany 8 172 0.8× 117 0.9× 52 0.4× 71 0.8× 139 1.7× 25 426

Countries citing papers authored by Sang-Suk Han

Since Specialization
Citations

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

Fields of papers citing papers by Sang-Suk Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sang-Suk Han. 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 Sang-Suk Han. The network helps show where Sang-Suk Han may publish in the future.

Co-authorship network of co-authors of Sang-Suk Han

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

All Works

11 of 11 papers shown
1.
Han, Sang-Suk, et al.. (2017). Automatic Extraction of Soft Tissue Tumor from Ultrasonography Using ART2 Based Intelligent Image Analysis. Current Medical Imaging Formerly Current Medical Imaging Reviews. 13(4). 5 indexed citations
2.
Kim, Kwang-Baek, et al.. (2015). Developing an Intelligent Automatic Appendix Extraction Method from Ultrasonography Based on Fuzzy ART and Image Processing. Computational and Mathematical Methods in Medicine. 2015. 1–10. 6 indexed citations
3.
Kim, Kwang J., et al.. (2014). Extraction of Sternocleidomastoid and Longus Capitis/Colli Muscle Using Cervical Vertebrae Ultrasound Images. Current Medical Imaging Formerly Current Medical Imaging Reviews. 10(2). 95–104. 4 indexed citations
5.
Park, Young Mi, et al.. (2010). Sonographic Findings of High-Grade and Non-High-Grade Ductal Carcinoma In Situ of the Breast. Journal of Ultrasound in Medicine. 29(12). 1687–1697. 43 indexed citations
6.
Lee, Sang-Chul, et al.. (2008). Determinants affecting patients loyalty in medical service: An empirical study on comparison with in-patients and out-patients using multi-group structural equation model. 13(4). 76–100. 1 indexed citations
7.
Lee, Sangchul, Yung‐Ho Suh, & Sang-Suk Han. (2007). Causal Relationship among Baldrige Health Care Criteria in Korean University Hospitals. Journal of the Korean society for quality management. 35(4). 1–15. 2 indexed citations
8.
Yoon, Junghee, et al.. (2005). Color Doppler Ultrasonography of a Pancreatic Arteriovenous Malformation. Journal of Ultrasound in Medicine. 24(1). 113–117. 12 indexed citations
9.
Rhim, Hyunchul, Kwon‐Ha Yoon, Jeong Min Lee, et al.. (2003). Major Complications after Radio-frequency Thermal Ablation of Hepatic Tumors: Spectrum of Imaging Findings. Radiographics. 23(1). 123–134. 266 indexed citations
10.
Han, Sang-Suk, et al.. (2001). The Use of Contrast-Enhanced Color Doppler Ultrasound in the Differentiation of Retinal Detachment from Vitreous Membrane. Korean Journal of Radiology. 2(4). 197–197. 16 indexed citations
11.
Han, Sang-Suk, et al.. (2000). A Study of the Degree of Duty Satisfaction According to the Nurses's Characteristics. 6(1). 5–18. 4 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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