Jung‐Hyun Yang

2.8k total citations
82 papers, 2.0k citations indexed

About

Jung‐Hyun Yang is a scholar working on Pathology and Forensic Medicine, Cancer Research and Surgery. According to data from OpenAlex, Jung‐Hyun Yang has authored 82 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Pathology and Forensic Medicine, 27 papers in Cancer Research and 22 papers in Surgery. Recurrent topics in Jung‐Hyun Yang's work include Breast Lesions and Carcinomas (25 papers), Breast Cancer Treatment Studies (19 papers) and Thyroid Cancer Diagnosis and Treatment (12 papers). Jung‐Hyun Yang is often cited by papers focused on Breast Lesions and Carcinomas (25 papers), Breast Cancer Treatment Studies (19 papers) and Thyroid Cancer Diagnosis and Treatment (12 papers). Jung‐Hyun Yang collaborates with scholars based in South Korea, United States and China. Jung‐Hyun Yang's co-authors include Seok Jin Nam, Jeong Eon Lee, Jee Soo Kim, Jun‐Ho Choe, Eun Yoon Cho, Young‐Hyuck Im, Se Kyung Lee, Jung‐Han Kim, Sung Mo Hur and Sangmin Kim and has published in prestigious journals such as Cancer Research, Scientific Reports and Annals of Oncology.

In The Last Decade

Jung‐Hyun Yang

76 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jung‐Hyun Yang South Korea 26 711 579 550 483 350 82 2.0k
H. Marsiglia France 23 908 1.3× 563 1.0× 1.0k 1.9× 531 1.1× 192 0.5× 113 2.2k
Mahdi Fallah Germany 26 1.1k 1.5× 361 0.6× 302 0.5× 424 0.9× 53 0.2× 82 2.6k
Jo Hermans Netherlands 20 613 0.9× 336 0.6× 332 0.6× 474 1.0× 33 0.1× 35 2.3k
Marco Bernini Italy 24 412 0.6× 256 0.4× 474 0.9× 990 2.0× 71 0.2× 78 2.0k
Ronald Reimer United States 20 487 0.7× 484 0.8× 118 0.2× 543 1.1× 126 0.4× 45 1.7k
Natia Esiashvili United States 27 534 0.8× 376 0.6× 144 0.3× 393 0.8× 77 0.2× 112 2.5k
Hedva Lerman Israel 24 750 1.1× 328 0.6× 371 0.7× 752 1.6× 36 0.1× 47 2.9k
Karen T. Pitman United States 27 893 1.3× 160 0.3× 123 0.2× 961 2.0× 52 0.1× 59 2.1k
Konstantinos Markou Greece 25 707 1.0× 232 0.4× 167 0.3× 1.0k 2.1× 38 0.1× 111 2.5k
Wendy W.J. de Leng Netherlands 30 526 0.7× 497 0.9× 314 0.6× 833 1.7× 59 0.2× 115 2.4k

Countries citing papers authored by Jung‐Hyun Yang

Since Specialization
Citations

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

Fields of papers citing papers by Jung‐Hyun Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jung‐Hyun Yang. 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 Jung‐Hyun Yang. The network helps show where Jung‐Hyun Yang may publish in the future.

Co-authorship network of co-authors of Jung‐Hyun Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Jung‐Hyun Yang. A scholar is included among the top collaborators of Jung‐Hyun Yang 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 Jung‐Hyun Yang. Jung‐Hyun Yang 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.
Kim, Jung-Hun, Hae‐Rim Kim, So Young Yoon, et al.. (2020). Ultrasonographic evaluation of chronic shoulder pain after breast cancer surgery: single center, cross-sectional study. Scientific Reports. 10(1). 16792–16792. 5 indexed citations
2.
Kang, Eunyoung, Hai‐Lin Park, Jong Won Lee, et al.. (2016). KOHBRA BRCA risk calculator (KOHCal): a model for predicting BRCA1 and BRCA2 mutations in Korean breast cancer patients. Journal of Human Genetics. 61(5). 365–371. 15 indexed citations
3.
Kim, Mi Young, et al.. (2015). Screening mammography-detected ductal carcinoma in situ: mammographic features based on breast cancer subtypes. Clinical Imaging. 39(6). 983–986. 13 indexed citations
4.
Park, Hai‐Lin, et al.. (2012). Nationwide survey of use of vacuum-assisted breast biopsy in South Korea.. PubMed. 32(12). 5459–64. 3 indexed citations
5.
Jang, Ja‐Hyun, Jeong Eon Lee, Min‐Jung Kwon, et al.. (2012). Spectra of BRCA1 and BRCA2 mutations in Korean patients with breast cancer: the importance of whole-gene sequencing. Journal of Human Genetics. 57(3). 212–215. 11 indexed citations
6.
Son, Byung Ho, Sei Hyun Ahn, Sung‐Won Kim, et al.. (2012). Prevalence of BRCA1 and BRCA2 mutations in non-familial breast cancer patients with high risks in Korea: The Korean Hereditary Breast Cancer (KOHBRA) Study. Breast Cancer Research and Treatment. 133(3). 1143–1152. 37 indexed citations
7.
Kim, Wan Wook, Jee Soo Kim, Sung Mo Hur, et al.. (2011). Is Robotic Surgery Superior to Endoscopic and Open Surgeries in Thyroid Cancer?. World Journal of Surgery. 35(4). 779–784. 96 indexed citations
8.
Kang, Seok Seon, Boo‐Kyung Han, Eun Young Ko, et al.. (2011). Methylene Blue Dye–Related Changes in the Breast After Sentinel Lymph Node Localization. Journal of Ultrasound in Medicine. 30(12). 1711–1721. 2 indexed citations
10.
Cho, Eun Yoon, Myung Hee Chang, Yoon‐La Choi, et al.. (2010). Potential candidate biomarkers for heterogeneity in triple-negative breast cancer (TNBC). Cancer Chemotherapy and Pharmacology. 68(3). 753–761. 24 indexed citations
11.
Park, Yeon Hee, Seung Tae Kim, Eun Yoon Cho, et al.. (2009). A risk stratification by hormonal receptors (ER, PgR) and HER-2 status in small (≤1 cm) invasive breast cancer: who might be possible candidates for adjuvant treatment?. Breast Cancer Research and Treatment. 119(3). 653–661. 53 indexed citations
12.
Lee, S.K., Jun‐Ho Choe, Jung Hee Shin, et al.. (2009). Sentinel lymph node biopsy in papillary thyroid cancer: Comparison study of blue dye method and combined radioisotope and blue dye method in papillary thyroid cancer. European Journal of Surgical Oncology. 35(9). 974–979. 38 indexed citations
13.
Kim, Jung Han, et al.. (2008). Thyroid Cancer That Developed Around the Operative Bed and Subcutaneous Tunnel After Endoscopic Thyroidectomy via a Breast Approach. Surgical Laparoscopy Endoscopy & Percutaneous Techniques. 18(2). 197–201. 32 indexed citations
14.
Choi, Young Jin, Yoon‐La Choi, Eun Yoon Cho, et al.. (2008). Expression of Bmi-1 protein in tumor tissues is associated with favorable prognosis in breast cancer patients. Breast Cancer Research and Treatment. 113(1). 83–93. 44 indexed citations
15.
Choi, Young‐Jin, et al.. (2006). Analysis of the Clinicopathological Features in the Micrometastasis and the Macrometastasis in Sentinel Lymph Node of Primary Breast Cancer. Journal of the Korean Surgical Society. 70(6). 419–424.
16.
Huh, Seung Jae, Youngyih Han, Won Park, & Jung‐Hyun Yang. (2005). Interfractional dose variation due to seromas in radiotherapy of breast cancer. Medical dosimetry. 30(1). 8–11. 11 indexed citations
17.
Shin, Myung‐Hee, et al.. (2004). validity of Self-Reported Weight, Height and Body Mass Index in a Hospital Based Breast Cancer Case-Control Study. 4(1). 45–51. 3 indexed citations
18.
Yang, Jung‐Hyun. (2003). Surgical Treatment of Breast Cancer. Journal of the Korean Medical Association. 46(6). 497–497.
19.
You, Cheol‐Hwan, et al.. (2003). Calculations of Z-R relationship with the cloud types. 대기. 13(1). 292–295.
20.
Han, Bing, Yeon Hyeon Choe, J M Park, et al.. (1999). Granulomatous mastitis: mammographic and sonographic appearances.. American Journal of Roentgenology. 173(2). 317–320. 104 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026