Ka Hee Yi

3.1k total citations
81 papers, 2.1k citations indexed

About

Ka Hee Yi is a scholar working on Endocrinology, Diabetes and Metabolism, Surgery and Genetics. According to data from OpenAlex, Ka Hee Yi has authored 81 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Endocrinology, Diabetes and Metabolism, 32 papers in Surgery and 12 papers in Genetics. Recurrent topics in Ka Hee Yi's work include Thyroid Cancer Diagnosis and Treatment (56 papers), Thyroid and Parathyroid Surgery (23 papers) and Thyroid Disorders and Treatments (19 papers). Ka Hee Yi is often cited by papers focused on Thyroid Cancer Diagnosis and Treatment (56 papers), Thyroid and Parathyroid Surgery (23 papers) and Thyroid Disorders and Treatments (19 papers). Ka Hee Yi collaborates with scholars based in South Korea, United States and Ethiopia. Ka Hee Yi's co-authors include Young Joo Park, Do Joon Park, Jae Hoon Moon, Sun Wook Cho, Hoon Choi, Kyu Eun Lee, Jung‐Ah Lim, Bo Youn Cho, Hwa Young Ahn and Young Jun Chai and has published in prestigious journals such as PLoS ONE, The Journal of Clinical Endocrinology & Metabolism and Cancer.

In The Last Decade

Ka Hee Yi

78 papers receiving 2.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ka Hee Yi South Korea 26 1.7k 782 306 296 277 81 2.1k
Jennifer A. Sipos United States 19 1.3k 0.8× 672 0.9× 318 1.0× 262 0.9× 286 1.0× 50 1.8k
Carlos Benbassat Israel 27 1.5k 0.9× 756 1.0× 243 0.8× 343 1.2× 237 0.9× 96 2.0k
Wataru Kitagawa Japan 24 1.5k 0.9× 1.1k 1.5× 225 0.7× 275 0.9× 289 1.0× 116 2.3k
Claire Schvartz France 20 2.4k 1.4× 1.1k 1.4× 347 1.1× 369 1.2× 449 1.6× 58 2.9k
Dario Tumino Italy 19 1.6k 0.9× 859 1.1× 226 0.7× 144 0.5× 276 1.0× 41 1.8k
Vincenzo Marotta Italy 25 1.2k 0.7× 421 0.5× 312 1.0× 570 1.9× 236 0.9× 64 1.9k
R. Mack Harrell United States 14 1.2k 0.7× 823 1.1× 119 0.4× 198 0.7× 276 1.0× 25 1.6k
Jonathan S. LoPresti United States 20 2.0k 1.2× 533 0.7× 334 1.1× 227 0.8× 175 0.6× 36 2.3k
Massimo Torlontano Italy 29 2.9k 1.7× 1.8k 2.4× 239 0.8× 196 0.7× 307 1.1× 44 3.2k
José Miguel Domínguez Chile 16 869 0.5× 498 0.6× 337 1.1× 416 1.4× 165 0.6× 68 1.6k

Countries citing papers authored by Ka Hee Yi

Since Specialization
Citations

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

Fields of papers citing papers by Ka Hee Yi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ka Hee Yi. 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 Ka Hee Yi. The network helps show where Ka Hee Yi may publish in the future.

Co-authorship network of co-authors of Ka Hee Yi

This figure shows the co-authorship network connecting the top 25 collaborators of Ka Hee Yi. A scholar is included among the top collaborators of Ka Hee Yi 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 Ka Hee Yi. Ka Hee Yi 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.
Ahn, Hwa Young, et al.. (2024). Rising Incidence and Comorbidities of Endogenous Hypothyroidism in Republic of Korea from 2004 to 2018: A Nationwide Population Study. Endocrinology and Metabolism. 39(6). 891–898. 1 indexed citations
3.
4.
Ahn, Hwa Young, Sun Wook Cho, Mi Young Lee, et al.. (2023). Prevalence, Treatment Status, and Comorbidities of Hyperthyroidism in Korea from 2003 to 2018: A Nationwide Population Study. Endocrinology and Metabolism. 38(4). 436–444. 10 indexed citations
5.
Yi, Ka Hee, Hwa Young Ahn, Jin Hwa Kim, et al.. (2023). 2023 Revised Korean Thyroid Association Guidelines for the Diagnosis and Management of Thyroid Disease during Pregnancy and Postpartum. 16(1). 51–88. 5 indexed citations
6.
Chung, Hyun Kyung, Eu Jeong Ku, Won Sang Yoo, et al.. (2023). 2023 Korean Thyroid Association Management Guidelines for Patients with Subclinical Hypothyroidism. 16(2). 214–215. 1 indexed citations
7.
Lee, Joon‐Hyop, Kwangsoo Kim, Young Jun Chai, et al.. (2021). Assessment of Inter-Institutional Post-Operative Hypoparathyroidism Status Using a Common Data Model. Journal of Clinical Medicine. 10(19). 4454–4454. 2 indexed citations
8.
Kim, Mijin, Sun Wook Cho, Young Joo Park, et al.. (2021). Clinicopathological Characteristics and Recurrence-Free Survival of Rare Variants of Papillary Thyroid Carcinomas in Korea: A Retrospective Study. Endocrinology and Metabolism. 36(3). 619–627. 5 indexed citations
9.
Lee, Joon‐Hyop, Kwangsoo Kim, Young Jun Chai, et al.. (2020). A national database analysis for factors associated with thyroid cancer occurrence. Scientific Reports. 10(1). 17791–17791. 7 indexed citations
10.
11.
Kong, Sung Hye, Jung‐Ah Lim, Young Shin Song, et al.. (2018). Star-Shaped Intense Uptake of 131I on Whole Body Scans Can Reflect Good Therapeutic Effects of Low-Dose Radioactive Iodine Treatment of 1.1 GBq. Endocrinology and Metabolism. 33(2). 228–228. 2 indexed citations
12.
Chai, Young Jun, Sang Mok Lee, June Young Choi, et al.. (2018). Significance of distance between tumor and thyroid capsule as an indicator for central lymph node metastasis in clinically node negative papillary thyroid carcinoma patients. PLoS ONE. 13(7). e0200166–e0200166. 12 indexed citations
13.
Chai, Young Jun, Jin Wook Yi, So Won Oh, et al.. (2016). Upregulation of SLC2 (GLUT) family genes is related to poor survival outcomes in papillary thyroid carcinoma: Analysis of data from The Cancer Genome Atlas. Surgery. 161(1). 188–194. 46 indexed citations
14.
Ha, Seunggyun, So Won Oh, Yu Kyeong Kim, et al.. (2015). Clinical Outcome of Remnant Thyroid Ablation with Low Dose Radioiodine in Korean Patients with Low to Intermediate-risk Thyroid Cancer. Journal of Korean Medical Science. 30(7). 876–876. 21 indexed citations
15.
Yi, Ka Hee, Soo Young Kim, Do‐Hoon Kim, et al.. (2015). The Korean guideline for thyroid cancer screening. Journal of Korean Medical Association. 58(4). 302–302. 25 indexed citations
16.
Lim, Jung‐Ah, Hyo Jeong Kim, Hwa Young Ahn, et al.. (2015). Influence of thyroid dysfunction on serum levels of angiopoietin-like protein 6. Metabolism. 64(10). 1279–1283. 9 indexed citations
17.
Cho, Sun Wook, Hoon Choi, Jung‐Ah Lim, et al.. (2013). Long-Term Prognosis of Differentiated Thyroid Cancer with Lung Metastasis in Korea and Its Prognostic Factors. Thyroid. 24(2). 277–286. 85 indexed citations
18.
Cho, Sun Wook, Eun Jung Lee, Hwa Young Ahn, et al.. (2012). Dickkopf-1 inhibits thyroid cancer cell survival and migration through regulation of β-catenin/E-cadherin signaling. Molecular and Cellular Endocrinology. 366(1). 90–98. 32 indexed citations
19.
Yi, Ka Hee. (2011). Updated Guidelines for the Management of Thyroid Nodule. The Korean Journal of Internal Medicine. 80(2). 158–161. 1 indexed citations
20.
Kim, Tae Yong, Kyung Won Kim, Tae Sik Jung, et al.. (2007). Prognostic factors for Korean patients with anaplastic thyroid carcinoma. Head & Neck. 29(8). 765–772. 73 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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