Heejin Bang

602 total citations
21 papers, 411 citations indexed

About

Heejin Bang is a scholar working on Molecular Biology, Pathology and Forensic Medicine and Oncology. According to data from OpenAlex, Heejin Bang has authored 21 papers receiving a total of 411 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 6 papers in Pathology and Forensic Medicine and 6 papers in Oncology. Recurrent topics in Heejin Bang's work include Radiomics and Machine Learning in Medical Imaging (3 papers), Cancer Mechanisms and Therapy (2 papers) and Renal cell carcinoma treatment (2 papers). Heejin Bang is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (3 papers), Cancer Mechanisms and Therapy (2 papers) and Renal cell carcinoma treatment (2 papers). Heejin Bang collaborates with scholars based in South Korea, United States and China. Heejin Bang's co-authors include Kyoung‐Mee Kim, Won Ki Kang, Sang Yun Ha, Cheol-Keun Park, Jeeyun Lee, Se Hoon Park, Seung Tae Kim, Soo Hyun Hwang, Woong‐Yang Park and Junhun Cho and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Annals of Oncology.

In The Last Decade

Heejin Bang

21 papers receiving 407 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Heejin Bang South Korea 10 217 142 100 95 68 21 411
Zebing Liu China 13 249 1.1× 190 1.3× 125 1.3× 134 1.4× 113 1.7× 38 514
Sumi Yun South Korea 12 190 0.9× 215 1.5× 150 1.5× 119 1.3× 47 0.7× 25 469
Marco Bono Italy 14 189 0.9× 185 1.3× 133 1.3× 125 1.3× 59 0.9× 33 446
Shih-Chen Yu Taiwan 14 217 1.0× 142 1.0× 117 1.2× 256 2.7× 48 0.7× 17 589
Aaron J. Schueneman United States 7 158 0.7× 183 1.3× 89 0.9× 109 1.1× 39 0.6× 8 377
H. Tsuda Japan 9 343 1.6× 180 1.3× 103 1.0× 55 0.6× 97 1.4× 15 554
Richard Ong Singapore 9 207 1.0× 116 0.8× 84 0.8× 110 1.2× 66 1.0× 20 413
Yuji Shimoda Japan 10 133 0.6× 210 1.5× 229 2.3× 132 1.4× 99 1.5× 26 410
Mina Waraya Japan 15 279 1.3× 196 1.4× 122 1.2× 79 0.8× 44 0.6× 30 514
Jennifer Carter United States 4 486 2.2× 206 1.5× 141 1.4× 146 1.5× 42 0.6× 7 669

Countries citing papers authored by Heejin Bang

Since Specialization
Citations

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

Fields of papers citing papers by Heejin Bang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Heejin Bang. 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 Heejin Bang. The network helps show where Heejin Bang may publish in the future.

Co-authorship network of co-authors of Heejin Bang

This figure shows the co-authorship network connecting the top 25 collaborators of Heejin Bang. A scholar is included among the top collaborators of Heejin Bang 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 Heejin Bang. Heejin Bang 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.
Lee, Seung Eun, et al.. (2023). NTRK Fusion in a Cohort of BRAF p. V600E Wild-Type Papillary Thyroid Carcinomas. Modern Pathology. 36(8). 100180–100180. 3 indexed citations
3.
Cho, Bum‐Joo, et al.. (2022). Automated Diagnosis of Cervical Intraepithelial Neoplasia in Histology Images via Deep Learning. Diagnostics. 12(2). 548–548. 15 indexed citations
4.
Bang, Heejin, et al.. (2022). Integrated bioinformatic analysis of gene expression profiling data to identify combinatorial biomarkers in inflammatory skin disease. Scientific Reports. 12(1). 5889–5889. 6 indexed citations
5.
Bang, Heejin, et al.. (2022). NTRK Fusions in 1113 Solid Tumors in a Single Institution. Diagnostics. 12(6). 1450–1450. 5 indexed citations
6.
Kim, Sang Yoon, et al.. (2022). Aggressive Clinical Deterioration of Recurrent Extramammary Paget’s Disease: A Case Report. SHILAP Revista de lepidopterología. 45(4). 1 indexed citations
7.
Lee, Ji Yun, Joo Hyun Kim, Heejin Bang, et al.. (2021). EGR1 as a potential marker of prognosis in extranodal NK/T-cell lymphoma. Scientific Reports. 11(1). 10342–10342. 8 indexed citations
8.
Bang, Heejin, Sanghui Park, Min-Sun Cho, et al.. (2019). Clinicopathologic study of 60 cases of urothelial neoplasms with inverted growth patterns: Reclassification by international consultation on urologic disease (ICUD) recommendations. Annals of Diagnostic Pathology. 44. 151433–151433. 6 indexed citations
9.
Bang, Heejin, Soomin Ahn, Seung Tae Kim, et al.. (2019). Correlation between RICTOR overexpression and amplification in advanced solid tumors. Pathology - Research and Practice. 216(1). 152734–152734. 6 indexed citations
10.
Kim, Hee Kyung, Heejin Bang, Hee Cheol Kim, et al.. (2018). MCT4 Expression Is a Potential Therapeutic Target in Colorectal Cancer with Peritoneal Carcinomatosis. Molecular Cancer Therapeutics. 17(4). 838–848. 40 indexed citations
11.
Kwon, Ah‐Young, et al.. (2017). Cytologic Characteristics of Thymic Adenocarcinoma with Enteric Differentiation: A Study of Four Fine-Needle Aspiration Specimens. Journal of Pathology and Translational Medicine. 51(5). 509–512. 5 indexed citations
12.
Jang, Jiryeon, Hee Kyung Kim, Heejin Bang, et al.. (2017). Antitumor Effect of AZD4547 in a Fibroblast Growth Factor Receptor 2–Amplified Gastric Cancer Patient–Derived Cell Model. Translational Oncology. 10(4). 469–475. 22 indexed citations
13.
Cho, Junhun, Jeeyun Lee, Heejin Bang, et al.. (2017). Programmed cell death-ligand 1 expression predicts survival in patients with gastric carcinoma with microsatellite instability. Oncotarget. 8(8). 13320–13328. 57 indexed citations
14.
Kim, Sun Young, TaeJin Ahn, Heejin Bang, et al.. (2017). Acquired resistance to LY2874455 in FGFR2-amplified gastric cancer through an emergence of novel FGFR2-ACSL5 fusion. Oncotarget. 8(9). 15014–15022. 45 indexed citations
15.
Kim, S. T., Su‐Young Kim, Samuel J. Klempner, et al.. (2016). Rapamycin-insensitive companion of mTOR (RICTOR) amplification defines a subset of advanced gastric cancer and is sensitive to AZD2014-mediated mTORC1/2 inhibition. Annals of Oncology. 28(3). 547–554. 52 indexed citations
16.
Yoon, Aera, Ji‐Yoon Ryu, Young‐Jae Cho, et al.. (2016). c-MET as a Potential Therapeutic Target in Ovarian Clear Cell Carcinoma. Scientific Reports. 6(1). 38502–38502. 34 indexed citations
17.
Bang, Heejin, Sang Yun Ha, Soo Hyun Hwang, & Cheol-Keun Park. (2015). Expression of PEG10 Is Associated with Poor Survival and Tumor Recurrence in Hepatocellular Carcinoma. Cancer Research and Treatment. 47(4). 844–852. 31 indexed citations
18.
Ha, Sang Yun, et al.. (2015). ATAD2 as a Poor Prognostic Marker for Hepatocellular Carcinoma after Curative Resection. Cancer Research and Treatment. 47(4). 853–861. 36 indexed citations
19.
Lee, Hyunwoo, et al.. (2014). Supratentorial Hemangioblastoma with Unusual Features. The Korean Journal of Pathology. 48(6). 462–465. 6 indexed citations
20.
Lee, Seung Eun, et al.. (2013). Epithelioid hemangioendothelioma with extensive cystic change and CAMTA1 rearrangement. Pathology International. 63(10). 502–505. 3 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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