Soo Yeon Hahn

5.3k total citations
99 papers, 2.5k citations indexed

About

Soo Yeon Hahn is a scholar working on Endocrinology, Diabetes and Metabolism, Surgery and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Soo Yeon Hahn has authored 99 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 73 papers in Endocrinology, Diabetes and Metabolism, 60 papers in Surgery and 28 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Soo Yeon Hahn's work include Thyroid Cancer Diagnosis and Treatment (73 papers), Head and Neck Anomalies (40 papers) and Thyroid and Parathyroid Surgery (37 papers). Soo Yeon Hahn is often cited by papers focused on Thyroid Cancer Diagnosis and Treatment (73 papers), Head and Neck Anomalies (40 papers) and Thyroid and Parathyroid Surgery (37 papers). Soo Yeon Hahn collaborates with scholars based in South Korea, United States and United Arab Emirates. Soo Yeon Hahn's co-authors include Jung Hee Shin, Eun Young Ko, Boo‐Kyung Han, Young Lyun Oh, Eun Sook Ko, Jae Hoon Chung, Tae Hyuk Kim, Sun Wook Kim, Jee Soo Kim and Yaeji Lim and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and The Journal of Clinical Endocrinology & Metabolism.

In The Last Decade

Soo Yeon Hahn

95 papers receiving 2.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Soo Yeon Hahn South Korea 29 1.4k 942 918 348 342 99 2.5k
Shane O. LeBeau United States 22 2.5k 1.8× 1.1k 1.2× 209 0.2× 279 0.8× 296 0.9× 29 2.8k
Eun Sook Ko South Korea 29 214 0.1× 258 0.3× 1.7k 1.8× 613 1.8× 367 1.1× 99 2.4k
François Bidault France 22 275 0.2× 522 0.6× 523 0.6× 93 0.3× 588 1.7× 86 1.7k
Tatjana Antic United States 33 392 0.3× 789 0.8× 1.2k 1.4× 80 0.2× 470 1.4× 135 3.3k
Michel Toubeau France 16 486 0.3× 382 0.4× 728 0.8× 282 0.8× 264 0.8× 37 1.5k
Giovanni Fellegara Italy 15 695 0.5× 460 0.5× 106 0.1× 123 0.4× 359 1.0× 43 1.4k
Silvia Taccogna Italy 13 1.2k 0.9× 947 1.0× 206 0.2× 84 0.2× 180 0.5× 28 1.6k
Beth S. Edeiken United States 17 244 0.2× 695 0.7× 247 0.3× 335 1.0× 281 0.8× 27 1.3k
Ki‐Wook Chung South Korea 30 2.1k 1.4× 1.3k 1.4× 291 0.3× 105 0.3× 312 0.9× 110 2.5k
Soo Youn Cho South Korea 22 194 0.1× 274 0.3× 161 0.2× 154 0.4× 445 1.3× 70 1.2k

Countries citing papers authored by Soo Yeon Hahn

Since Specialization
Citations

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

Fields of papers citing papers by Soo Yeon Hahn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Soo Yeon Hahn

This figure shows the co-authorship network connecting the top 25 collaborators of Soo Yeon Hahn. A scholar is included among the top collaborators of Soo Yeon Hahn 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 Soo Yeon Hahn. Soo Yeon Hahn 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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Lee, Ji Ye, Min Kyoung Lee, Hyun Kyung Lim, et al.. (2024). Standardized Ultrasound Evaluation for Active Surveillance of Low-Risk Thyroid Microcarcinoma in Adults: 2024 Korean Society of Thyroid Radiology Consensus Statement. PubMed. 85(6). 1060–1060. 1 indexed citations
4.
Shin, Jung Hee, et al.. (2024). The Parathyroid Gland: An Overall Review of the Hidden Organ for Radiologists. SHILAP Revista de lepidopterología. 85(2). 327–327.
5.
Oh, Young Lyun, et al.. (2023). Comparison of clinicopathological characteristics and survival between symptomatic and asymptomatic anaplastic thyroid carcinoma. Scientific Reports. 13(1). 3264–3264. 5 indexed citations
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Shin, Jung Hee, et al.. (2023). Subcategorization of intermediate suspicion thyroid nodules based on suspicious ultrasonographic findings. ULTRASONOGRAPHY. 42(2). 307–313. 3 indexed citations
8.
Park, Hyunju, Hyeong Chan Shin, Chang‐Seok Ki, et al.. (2021). Molecular classification of follicular thyroid carcinoma based on TERT promoter mutations. Modern Pathology. 35(2). 186–192. 31 indexed citations
9.
Kim, Hosu, Tae Hyuk Kim, Jun‐Ho Choe, et al.. (2017). Patterns of Initial Recurrence in Completely Resected Papillary Thyroid Carcinoma. Thyroid. 27(7). 908–914. 55 indexed citations
10.
Ahn, Soomin, Tae Hyuk Kim, Sun Wook Kim, et al.. (2017). Comprehensive screening for PD-L1 expression in thyroid cancer. Endocrine Related Cancer. 24(2). 97–106. 133 indexed citations
11.
Hahn, Soo Yeon, Eun Sook Ko, Boo‐Kyung Han, et al.. (2016). Analysis of factors influencing the degree of detectability on diffusion-weighted MRI and diffusion background signals in patients with invasive breast cancer. Medicine. 95(27). e4086–e4086. 21 indexed citations
12.
Hahn, Soo Yeon, et al.. (2016). The Diagnostic Performance of Thyroid US in Each Category of the Bethesda System for Reporting Thyroid Cytopathology. PLoS ONE. 11(6). e0155898–e0155898. 15 indexed citations
13.
Hahn, Soo Yeon, Jung Hee Shin, Hyun Kyung Lim, et al.. (2016). Preoperative differentiation between noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) and non-NIFTP. Clinical Endocrinology. 86(3). 444–450. 61 indexed citations
14.
Ko, Eun Sook, Rock Bum Kim, Boo‐Kyung Han, et al.. (2015). Effect of menstrual cycle and menopausal status on apparent diffusion coefficient values and detectability of invasive ductal carcinoma on diffusion-weighted MRI. Breast Cancer Research and Treatment. 149(3). 751–759. 14 indexed citations
15.
Ko, Eun Sook, Boo‐Kyung Han, Rock Bum Kim, et al.. (2013). Analysis of Factors that Influence the Accuracy of Magnetic Resonance Imaging for Predicting Response after Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer. Annals of Surgical Oncology. 20(8). 2562–2568. 58 indexed citations
16.
Rhee, Sun Jung, et al.. (2013). Follicular Variant of Papillary Thyroid Carcinoma: Distinct Biologic Behavior Based on Ultrasonographic Features. Thyroid. 24(4). 683–688. 39 indexed citations
17.
Seo, Jeong-Meen, Eun Sook Ko, Boo‐Kyung Han, et al.. (2013). Automated volumetric breast density estimation: A comparison with visual assessment. Clinical Radiology. 68(7). 690–695. 45 indexed citations
18.
Lee, Mi Hee, Eun Young Ko, Boo‐Kyung Han, et al.. (2013). Sonographic findings of pure ductal carcinoma in situ. Journal of Clinical Ultrasound. 41(8). 465–471. 14 indexed citations
19.
Nam, Sang Yu, Eun Sook Ko, Boo‐Kyung Han, et al.. (2013). Ultrasonographic hyperechoic lesions of the breast: are they always benign?. Acta Radiologica. 56(1). 18–24. 6 indexed citations
20.
Choi, Yoon Jung, Eun Young Ko, Boo‐Kyung Han, et al.. (2009). High-resolution ultrasonographic features of axillary lymph node metastasis in patients with breast cancer. The Breast. 18(2). 119–122. 78 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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