Hye Shin Ahn

2.3k total citations
68 papers, 825 citations indexed

About

Hye Shin Ahn is a scholar working on Surgery, Radiology, Nuclear Medicine and Imaging and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Hye Shin Ahn has authored 68 papers receiving a total of 825 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Surgery, 25 papers in Radiology, Nuclear Medicine and Imaging and 24 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Hye Shin Ahn's work include Thyroid Cancer Diagnosis and Treatment (24 papers), MRI in cancer diagnosis (14 papers) and Breast Lesions and Carcinomas (13 papers). Hye Shin Ahn is often cited by papers focused on Thyroid Cancer Diagnosis and Treatment (24 papers), MRI in cancer diagnosis (14 papers) and Breast Lesions and Carcinomas (13 papers). Hye Shin Ahn collaborates with scholars based in South Korea, United States and Germany. Hye Shin Ahn's co-authors include Mirinae Seo, Sung Hee Park, Sun Mi Kim, Mijung Jang, Bo La Yun, Jung Hwan Baek, Jong Beum Lee, Byung Ihn Choi, Soo Jin Kim and Geum Ok Baek and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Hye Shin Ahn

64 papers receiving 815 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hye Shin Ahn South Korea 16 373 302 247 154 134 68 825
Meiping Shen China 15 204 0.5× 139 0.5× 146 0.6× 208 1.4× 274 2.0× 39 752
Jin Wook Yi South Korea 19 387 1.0× 493 1.6× 42 0.2× 83 0.5× 154 1.1× 75 890
Luca Del Viscovo Italy 16 308 0.8× 407 1.3× 151 0.6× 85 0.6× 51 0.4× 32 1.2k
Federica Vianello Italy 18 511 1.4× 174 0.6× 58 0.2× 148 1.0× 219 1.6× 44 828
Michael J. Campbell United States 13 307 0.8× 296 1.0× 68 0.3× 61 0.4× 40 0.3× 35 560
Umberto Maestroni Italy 16 78 0.2× 360 1.2× 80 0.3× 106 0.7× 126 0.9× 79 772
Toshihiro Nozato Japan 22 52 0.1× 278 0.9× 294 1.2× 57 0.4× 184 1.4× 78 1.2k
Yingtai Chen China 17 155 0.4× 362 1.2× 98 0.4× 147 1.0× 123 0.9× 99 1.1k
Jordan Andrews Australia 13 161 0.4× 399 1.3× 179 0.7× 94 0.6× 107 0.8× 35 644
Isabella Reccia United Kingdom 18 249 0.7× 503 1.7× 35 0.1× 82 0.5× 265 2.0× 48 1.1k

Countries citing papers authored by Hye Shin Ahn

Since Specialization
Citations

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

Fields of papers citing papers by Hye Shin Ahn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hye Shin Ahn. 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 Hye Shin Ahn. The network helps show where Hye Shin Ahn may publish in the future.

Co-authorship network of co-authors of Hye Shin Ahn

This figure shows the co-authorship network connecting the top 25 collaborators of Hye Shin Ahn. A scholar is included among the top collaborators of Hye Shin Ahn 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 Hye Shin Ahn. Hye Shin Ahn 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.
Ahn, Hye Shin, Dong Gyu Na, & Ji‐hoon Kim. (2024). Risk Stratification of Thyroid Nodules Diagnosed as Bethesda Category III by Ultrasound, Size, and Cytology. Korean Journal of Radiology. 25(10). 924–924.
2.
3.
Ahn, Hye Shin, So Lyung Jung, Jung Hwan Baek, Jin Yong Sung, & Ji‐hoon Kim. (2023). Training of Radiofrequency Ablation for Thyroid Nodules in Korea: Current and Future Perspective. SHILAP Revista de lepidopterología. 84(5). 1009–1009. 1 indexed citations
4.
Yun, Bo La, Mijung Jang, Hye Shin Ahn, et al.. (2021). Using a mobile device for margin assessment of specimen mammography in breast-conserving surgery. Medicine. 100(38). e27243–e27243. 2 indexed citations
5.
Chung, Sae Rom, Hye Shin Ahn, Young Jun Choi, et al.. (2021). Diagnostic Performance of the Modified Korean Thyroid Imaging Reporting and Data System for Thyroid Malignancy: A Multicenter Validation Study. Korean Journal of Radiology. 22(9). 1579–1579. 20 indexed citations
6.
Lim, Sun Gyo, Jae Bum Park, Kee Myung Lee, et al.. (2020). Release of hazardous volatile organic compounds from endoscopic submucosal dissection. Surgical Endoscopy. 35(8). 4520–4527.
7.
Kim, Sun Mi, et al.. (2020). Comparison of One- and Two-Region of Interest Strain Elastography Measurements in the Differential Diagnosis of Breast Masses. Korean Journal of Radiology. 21(4). 431–431. 3 indexed citations
8.
Han, Hee-Soo, Hye Shin Ahn, Yu‐Kyong Shin, et al.. (2020). Chemical Constituents of the Leaves of Campanula takesimana (Korean Bellflower) and Their Inhibitory Effects on LPS-induced PGE2 Production. Plants. 9(9). 1232–1232. 7 indexed citations
9.
Kim, Youngjune, Sun Mi Kim, Bo La Yun, et al.. (2020). False-negative results on computer-aided detection software in preoperative automated breast ultrasonography of breast cancer patients. ULTRASONOGRAPHY. 40(1). 83–92. 6 indexed citations
10.
Ha, Su Min, Yun Jae Chung, Hye Shin Ahn, Jung Hwan Baek, & Sung Bin Park. (2019). Echogenic foci in thyroid nodules: diagnostic performance with combination of TIRADS and echogenic foci. BMC Medical Imaging. 19(1). 28–28. 15 indexed citations
11.
Yun, Gabin, Sun Mi Kim, Bo La Yun, Hye Shin Ahn, & Mijung Jang. (2018). Reliability of automated versus handheld breast ultrasound examinations of suspicious breast masses. ULTRASONOGRAPHY. 38(3). 264–271. 11 indexed citations
12.
13.
Ha, Su Min, Hye Shin Ahn, Hye Shin Ahn, et al.. (2017). Validation of Three Scoring Risk-Stratification Models for Thyroid Nodules. Thyroid. 27(12). 1550–1557. 28 indexed citations
14.
Ryoo, Inseon, Dong Wook Kim, Chang Yoon Lee, et al.. (2017). Analysis of postoperative ultrasonography surveillance after total thyroidectomy in patients with papillary thyroid carcinoma: a multicenter study. Acta Radiologica. 59(2). 196–203. 9 indexed citations
15.
Yoo, Jeongin, Hye Shin Ahn, Soo Jin Kim, et al.. (2017). Evaluation of Diagnostic Performance of Screening Thyroid Ultrasonography and Imaging Findings of Screening-Detected Thyroid Cancer. Cancer Research and Treatment. 50(1). 11–18. 13 indexed citations
16.
Ahn, Hye Shin, Soo Jin Kim, Sung Hee Park, & Mirinae Seo. (2016). Radiofrequency ablation of benign thyroid nodules: evaluation of the treatment efficacy using ultrasonography. ULTRASONOGRAPHY. 35(3). 244–252. 47 indexed citations
17.
Yin, Jun, et al.. (2016). Quantitative Analysis of Taxifolin, (+)-Catechin and Procyanidin B1 from the Preparation of Pinus densiflora (PineXol®). Korean Journal of Pharmacognosy. 47(3). 246–250. 4 indexed citations
18.
Yun, Bo La, Sun Mi Kim, Mijung Jang, et al.. (2015). Does Adding Diffuse Optical Tomography to Sonography Improve Differentiation Between Benign and Malignant Breast Lesions?. Journal of Ultrasound in Medicine. 34(5). 749–757. 3 indexed citations
19.
Ahn, Hye Shin, Sun Mi Kim, Mijung Jang, et al.. (2013). Comparison of Sonography With Sonographically Guided Fine‐Needle Aspiration Biopsy and Core‐Needle Biopsy for Initial Axillary Staging of Breast Cancer. Journal of Ultrasound in Medicine. 32(12). 2177–2184. 21 indexed citations
20.
Ahn, Hye Shin, Sun Mi Kim, Bo La Yun, et al.. (2013). The Unusual Ultrasound Features of a Breast Cholesterol Granuloma Manifesting as an Intracystic Mass: Case Report and Literature Review. Korean Journal of Radiology. 14(2). 179–179. 10 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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