Su Yeon Ko

442 total citations
21 papers, 339 citations indexed

About

Su Yeon Ko is a scholar working on Surgery, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Su Yeon Ko has authored 21 papers receiving a total of 339 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Surgery, 5 papers in Pulmonary and Respiratory Medicine and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Su Yeon Ko's work include Thyroid Cancer Diagnosis and Treatment (5 papers), Head and Neck Anomalies (2 papers) and Cancer and Skin Lesions (2 papers). Su Yeon Ko is often cited by papers focused on Thyroid Cancer Diagnosis and Treatment (5 papers), Head and Neck Anomalies (2 papers) and Cancer and Skin Lesions (2 papers). Su Yeon Ko collaborates with scholars based in South Korea and United States. Su Yeon Ko's co-authors include Eun‐Kyung Kim, Hee Jung Moon, Jin Young Kwak, Hee Sun Park, Young Jun Kim, Hae Jeong Jeon, Sung Il Jung, Min Woo Lee, Nam Chol Yu and Min Jung Kim and has published in prestigious journals such as SHILAP Revista de lepidopterología, American Journal of Roentgenology and Journal of Neurology.

In The Last Decade

Su Yeon Ko

19 papers receiving 336 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Su Yeon Ko South Korea 9 135 98 90 88 73 21 339
Jung Min Bae South Korea 8 140 1.0× 22 0.2× 66 0.7× 36 0.4× 67 0.9× 15 308
Zhihui Fan China 13 142 1.1× 76 0.8× 164 1.8× 184 2.1× 189 2.6× 28 493
Chaoxue Zhang China 10 144 1.1× 14 0.1× 44 0.5× 69 0.8× 79 1.1× 70 314
Katherine To’o United States 10 167 1.2× 14 0.1× 129 1.4× 90 1.0× 102 1.4× 12 492
Jianqiao Zhou China 12 356 2.6× 257 2.6× 109 1.2× 16 0.2× 53 0.7× 39 594
Changli Li China 8 201 1.5× 67 0.7× 150 1.7× 8 0.1× 55 0.8× 11 394
Nami Choi South Korea 15 349 2.6× 213 2.2× 145 1.6× 13 0.1× 51 0.7× 33 671
Qiu-Cheng Wang China 5 193 1.4× 53 0.5× 123 1.4× 14 0.2× 24 0.3× 7 422
Khaled Y. Elbanna Canada 10 107 0.8× 21 0.2× 113 1.3× 31 0.4× 49 0.7× 24 303
Yongping Lu China 6 254 1.9× 10 0.1× 49 0.5× 143 1.6× 143 2.0× 9 440

Countries citing papers authored by Su Yeon Ko

Since Specialization
Citations

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

Fields of papers citing papers by Su Yeon Ko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Su Yeon Ko. 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 Su Yeon Ko. The network helps show where Su Yeon Ko may publish in the future.

Co-authorship network of co-authors of Su Yeon Ko

This figure shows the co-authorship network connecting the top 25 collaborators of Su Yeon Ko. A scholar is included among the top collaborators of Su Yeon Ko 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 Su Yeon Ko. Su Yeon Ko 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.
Ko, Su Yeon & Min Jung Kim. (2023). Associations of age, body mass index, and breast size with mammographic breast density in Korean women. SHILAP Revista de lepidopterología. 20(1). 21–31. 1 indexed citations
2.
Choi, Guk Myung, et al.. (2023). Comparison of True and Virtual Non-Contrast Images of Liver Obtained with Single-Source Twin Beam and Dual-Source Dual-Energy CT. SHILAP Revista de lepidopterología. 84(1). 170–170.
3.
Lee, So Young, et al.. (2023). Rapidly Progressing Dysphagia After Thoracic Spinal Cord Injury in a Patient With Ankylosing Spondylitis: A Case Report. Geriatric Orthopaedic Surgery & Rehabilitation. 14. 2533867577–2533867577.
4.
5.
Kim, Jeong Jae, et al.. (2022). Renal Epithelioid Angiomyolipoma with Epithelial Cysts Mimicking Cystic Renal Cell Carcinoma: A Case Report of Combination of Two Rare Entities. SHILAP Revista de lepidopterología. 83(5). 1109–1109. 3 indexed citations
6.
Ko, Su Yeon, et al.. (2021). Macrocystic lymphatic malformation of the chest wall and axilla: A case report in a 45-year-old man. SHILAP Revista de lepidopterología. 17(1). 152–155. 2 indexed citations
7.
Ko, Su Yeon, Ji Hye Lee, Jung Hyun Yoon, et al.. (2019). Deep convolutional neural network for the diagnosis of thyroid nodules on ultrasound. Head & Neck. 41(4). 885–891. 76 indexed citations
8.
Ko, Su Yeon, et al.. (2018). Bilateral diffuse tumorous pseudoangiomatous stromal hyperplasia treated with bilateral mastectomy in a 40-year-old woman. Radiology Case Reports. 13(6). 1271–1275. 2 indexed citations
9.
Lee, Minah, et al.. (2017). Spectrum of imaging findings of chronic granulomatous disease: a single center experience. Diagnostic and Interventional Radiology. 23(6). 472–477. 7 indexed citations
10.
Moon, Hee Jung, et al.. (2015). Thyroid nodules ≤5 mm on ultrasonography: are they “leave me alone” lesions?. Endocrine. 49(3). 735–744. 7 indexed citations
11.
Ko, Su Yeon, Eun‐Kyung Kim, Hee Jung Moon, et al.. (2015). Application of Thyroid Imaging Reporting and Data System in the Ultrasound Assessment of Thyroid Nodules According to Physician Experience. Ultrasound Quarterly. 32(2). 126–131. 9 indexed citations
12.
Park, Ji Kang, et al.. (2014). Usefulness of contrast enhanced FLAIR imaging for predicting the severity of meningitis. Journal of Neurology. 261(4). 817–822. 10 indexed citations
13.
Ko, Su Yeon, Eun‐Kyung Kim, Min Jung Kim, & Hee Jung Moon. (2014). Mammographic Density Estimation with Automated Volumetric Breast Density Measurement. Korean Journal of Radiology. 15(3). 313–313. 29 indexed citations
14.
Ko, Su Yeon, Young Jun Kim, Hee Sun Park, et al.. (2013). Sonographic findings of ectopic prostatic tissue in the bladder: a case report and review of the literature. Clinical Imaging. 37(4). 778–779. 2 indexed citations
15.
Ko, Su Yeon, Hye Sun Lee, Eun‐Kyung Kim, & Jin Young Kwak. (2013). Application of the Thyroid Imaging Reporting and Data System in thyroid ultrasonography interpretation by less experienced physicians. ULTRASONOGRAPHY. 33(1). 49–57. 26 indexed citations
16.
Ko, Su Yeon, Eun‐Kyung Kim, Ji Min Sung, Hee Jung Moon, & Jin Young Kwak. (2013). Diagnostic Performance of Ultrasound and Ultrasound Elastography with Respect to Physician Experience. Ultrasound in Medicine & Biology. 40(5). 854–863. 26 indexed citations
17.
18.
Park, Hee Sun, et al.. (2012). Benign regional lymph nodes in gastric cancer on multidetector row CT. Acta Radiologica. 53(5). 501–507. 24 indexed citations
19.
Park, Sang Woo, Su Yeon Ko, So Young Yoon, et al.. (2010). Transcatheter arterial embolization for hemoperitoneum: unusual manifestation of iatrogenic injury to abdominal muscular arteries. Abdominal Imaging. 36(1). 74–78. 15 indexed citations
20.
Lee, Min Woo, Young Jun Kim, Hee Sun Park, et al.. (2010). Targeted Sonography for Small Hepatocellular Carcinoma Discovered by CT or MRI: Factors Affecting Sonographic Detection. American Journal of Roentgenology. 194(5). W396–W400. 91 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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