Jeoung Won Bae

1.2k total citations
67 papers, 890 citations indexed

About

Jeoung Won Bae is a scholar working on Cancer Research, Surgery and Oncology. According to data from OpenAlex, Jeoung Won Bae has authored 67 papers receiving a total of 890 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Cancer Research, 23 papers in Surgery and 23 papers in Oncology. Recurrent topics in Jeoung Won Bae's work include Breast Cancer Treatment Studies (19 papers), Breast Lesions and Carcinomas (16 papers) and Thyroid and Parathyroid Surgery (12 papers). Jeoung Won Bae is often cited by papers focused on Breast Cancer Treatment Studies (19 papers), Breast Lesions and Carcinomas (16 papers) and Thyroid and Parathyroid Surgery (12 papers). Jeoung Won Bae collaborates with scholars based in South Korea, Japan and Italy. Jeoung Won Bae's co-authors include Hye Yoon Lee, Hoon Yub Kim, Jae Bok Lee, Gil Soo Son, Sang Uk Woo, Seung Pil Jung, Insun Kim, Jung Ah Lee, Kyu Eun Lee and Ji Young You and has published in prestigious journals such as Cancer Research, Annals of Surgical Oncology and Breast Cancer Research and Treatment.

In The Last Decade

Jeoung Won Bae

62 papers receiving 877 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jeoung Won Bae South Korea 18 359 291 214 204 164 67 890
Chan Heun Park South Korea 19 398 1.1× 238 0.8× 283 1.3× 183 0.9× 119 0.7× 52 964
Yong Lai Park South Korea 20 366 1.0× 259 0.9× 329 1.5× 187 0.9× 141 0.9× 47 1.0k
Sien‐Yi Sheu Germany 19 283 0.8× 196 0.7× 218 1.0× 513 2.5× 68 0.4× 50 1.0k
Yoon Jung Choi South Korea 23 515 1.4× 235 0.8× 128 0.6× 451 2.2× 188 1.1× 49 1.1k
Kwang‐Sun Suh South Korea 15 105 0.3× 235 0.8× 183 0.9× 90 0.4× 71 0.4× 55 802
Saif S. Al-Sobhi Saudi Arabia 17 205 0.6× 260 0.9× 228 1.1× 379 1.9× 172 1.0× 66 881
Sameer A. Dhayat Germany 17 312 0.9× 341 1.2× 248 1.2× 61 0.3× 56 0.3× 30 1.1k
Cheng–Lung Hsu Taiwan 17 204 0.6× 130 0.4× 284 1.3× 162 0.8× 66 0.4× 33 1.2k
Hye Yoon Lee South Korea 18 510 1.4× 171 0.6× 91 0.4× 189 0.9× 57 0.3× 51 903
Rixiang Gong China 21 458 1.3× 144 0.5× 193 0.9× 671 3.3× 38 0.2× 55 936

Countries citing papers authored by Jeoung Won Bae

Since Specialization
Citations

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

Fields of papers citing papers by Jeoung Won Bae

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jeoung Won Bae. 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 Jeoung Won Bae. The network helps show where Jeoung Won Bae may publish in the future.

Co-authorship network of co-authors of Jeoung Won Bae

This figure shows the co-authorship network connecting the top 25 collaborators of Jeoung Won Bae. A scholar is included among the top collaborators of Jeoung Won Bae 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 Jeoung Won Bae. Jeoung Won Bae 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.
You, Ji Young, Kyong Hwa Park, Eun Sook Lee, et al.. (2023). Determining the Factors Predicting the Response to Anti-HER2 Therapy in HER2-Positive Breast Cancer Patients. Cancer Control. 30. 2905559720–2905559720.
2.
Bae, Soo Youn, Ji Young You, Hong Kyu Kim, et al.. (2018). Lymph node ratio as an alternative to pN staging for predicting prognosis after neoadjuvant chemotherapy in breast cancer. The Kaohsiung Journal of Medical Sciences. 34(6). 341–347. 14 indexed citations
3.
Cho, Kyu Ran, Eun Kyung Park, Bo Kyoung Seo, et al.. (2016). Significance of Additional Non-Mass Enhancement in Patients with Breast Cancer on Preoperative 3T Dynamic Contrast Enhanced MRI of the Breast. Iranian Journal of Radiology. 13(1). e30909–e30909. 25 indexed citations
4.
Chang, Young Woo, Hwan Soo Kim, Seung Pil Jung, et al.. (2016). Pre-ablation stimulated thyroglobulin is a better predictor of recurrence in pathological N1a papillary thyroid carcinoma than the lymph node ratio. International Journal of Clinical Oncology. 21(5). 862–868. 12 indexed citations
5.
Park, Eunkyung, Kyu Ran Cho, Bo Kyoung Seo, et al.. (2016). Additional Value of Diffusion-Weighted Imaging to Evaluate Prognostic Factors of Breast Cancer: Correlation with the Apparent Diffusion Coefficient. Iranian Journal of Radiology. 13(1). e33133–e33133. 29 indexed citations
6.
Jung, Seung Pil, Hye Yoon Lee, Jeoung Won Bae, & Hoon Yub Kim. (2015). Medullary Thyroid Carcinoma Metastasis to the Breast and Axillary Lymph Nodes. Indian Journal of Surgery. 77(4). 329–331. 2 indexed citations
7.
Lee, Hye Yoon, et al.. (2015). Robotic Thyroid Surgery for Papillary Thyroid Carcinoma. Surgical Laparoscopy Endoscopy & Percutaneous Techniques. 25(1). 27–32. 5 indexed citations
8.
Kim, Hoon Yub, Hye Yoon Lee, Seung Pil Jung, et al.. (2015). Predictive factors for difficult robotic thyroidectomy using the bilateral axillo‐breast approach. Head & Neck. 38(S1). E954–60. 14 indexed citations
9.
Lee, Hye Yoon, et al.. (2014). The Safety of Transoral Periosteal Thyroidectomy: Results of Swine Models. Journal of Laparoendoscopic & Advanced Surgical Techniques. 24(5). 312–317. 25 indexed citations
10.
Lee, Hye Yoon, Ji Young You, Sang Uk Woo, et al.. (2014). Transoral periosteal thyroidectomy: cadaver to human. Surgical Endoscopy. 29(4). 898–904. 72 indexed citations
11.
Jung, Seung Pil, Kang Min Han, Seok Jin Kim, et al.. (2014). Primary Follicular Lymphoma in a Male Breast: A Case Report. Cancer Research and Treatment. 46(1). 104–107. 3 indexed citations
12.
Jung, Seung Pil, Yoon Lee, Kang Min Han, et al.. (2013). Breast Metastasis from Rhabdomyosarcoma of the Anus in an Adolescent Female. Journal of Breast Cancer. 16(3). 345–345. 2 indexed citations
13.
Kim, Woo Young, Sang Uk Woo, Gil Soo Son, Jae Bok Lee, & Jeoung Won Bae. (2013). Breast Sparganosis. The Breast Journal. 19(2). 208–209. 1 indexed citations
14.
15.
Lee, Jung Ah, Jeoung Won Bae, Sang Uk Woo, Hyunchul Kim, & Chul Hwan Kim. (2011). D2-40, Podoplanin, and CD31 as a Prognostic Predictor in Invasive Ductal Carcinomas of the Breast. Journal of Breast Cancer. 14(2). 104–104. 20 indexed citations
16.
Lee, Jung Ah, et al.. (2010). Triple negative breast cancer in Korea-distinct biology with different impact of prognostic factors on survival. Breast Cancer Research and Treatment. 123(1). 177–187. 43 indexed citations
17.
Lee, Jung Ah, Jeoung Won Bae, Sang Uk Woo, Hyunchul Kim, & Chul Hwan Kim. (2010). Correlation between COX-2 Expression and Hormone Receptors in Invasive Ductal Breast Cancer. Journal of the Korean Surgical Society. 78(3). 140–140. 4 indexed citations
18.
Kim, Jin, et al.. (2006). Squamous Cell Carcinoma Arising in Recurrent Epidermal Cyst.. Journal of the Korean Surgical Society. 71(1). 79–81.
19.
Kim, Joon, et al.. (2005). RT-PCR amplification of CK 20 mRNA in the peripheral blood of breast cancer patients: correlation with established prognostic parameters. Biomedicine & Pharmacotherapy. 59. S380–S383. 2 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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