Sang Hoon Bae

872 total citations
58 papers, 589 citations indexed

About

Sang Hoon Bae is a scholar working on Surgery, Pulmonary and Respiratory Medicine and Pathology and Forensic Medicine. According to data from OpenAlex, Sang Hoon Bae has authored 58 papers receiving a total of 589 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Surgery, 12 papers in Pulmonary and Respiratory Medicine and 9 papers in Pathology and Forensic Medicine. Recurrent topics in Sang Hoon Bae's work include Infectious Diseases and Tuberculosis (5 papers), Breast Lesions and Carcinomas (5 papers) and Traffic Prediction and Management Techniques (4 papers). Sang Hoon Bae is often cited by papers focused on Infectious Diseases and Tuberculosis (5 papers), Breast Lesions and Carcinomas (5 papers) and Traffic Prediction and Management Techniques (4 papers). Sang Hoon Bae collaborates with scholars based in South Korea, United States and Ethiopia. Sang Hoon Bae's co-authors include Hyo Keun Lim, Dae Young Yoon, Chul Soon Choi, Young Lan Seo, Eun Joo Yun, Kyoung Ja Lim, Suk Ki Chang, Jin Wook Chung, Byung Ihn Choi and Myung Jin Chung and has published in prestigious journals such as Annals of the New York Academy of Sciences, American Journal of Roentgenology and Transportation Research Part D Transport and Environment.

In The Last Decade

Sang Hoon Bae

47 papers receiving 565 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sang Hoon Bae South Korea 13 309 140 93 85 82 58 589
Su‐Hua Wu China 16 192 0.6× 22 0.2× 124 1.3× 108 1.3× 63 0.8× 37 1.1k
Murat Akın Türkiye 16 534 1.7× 31 0.2× 154 1.7× 16 0.2× 174 2.1× 53 815
Francesco Verde Italy 18 211 0.7× 31 0.2× 288 3.1× 580 6.8× 114 1.4× 50 1.1k
Faqin Lv China 16 259 0.8× 50 0.4× 99 1.1× 134 1.6× 53 0.6× 64 695
Yu‐Ting Cheng Taiwan 17 199 0.6× 39 0.3× 190 2.0× 81 1.0× 67 0.8× 72 774
Bojan Biočina Croatia 19 517 1.7× 75 0.5× 150 1.6× 72 0.8× 28 0.3× 82 987
Horacio D’Agostino United States 14 272 0.9× 19 0.1× 136 1.5× 51 0.6× 77 0.9× 37 490
Berhane Worku United States 16 372 1.2× 100 0.7× 138 1.5× 19 0.2× 19 0.2× 71 779
M H Jamison United Kingdom 8 299 1.0× 22 0.2× 87 0.9× 28 0.3× 50 0.6× 14 485
Scott Marwin United States 14 822 2.7× 146 1.0× 39 0.4× 53 0.6× 16 0.2× 41 1.0k

Countries citing papers authored by Sang Hoon Bae

Since Specialization
Citations

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

Fields of papers citing papers by Sang Hoon Bae

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sang Hoon Bae

This figure shows the co-authorship network connecting the top 25 collaborators of Sang Hoon Bae. A scholar is included among the top collaborators of Sang Hoon 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 Sang Hoon Bae. Sang Hoon 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.
Bae, Sang Hoon, et al.. (2021). Speed Prediction of Urban Freeway Using LSTM and CNN-LSTM Neural Network. The Journal of The Korea Institute of Intelligent Transport Systems. 20(1). 86–99. 2 indexed citations
2.
Bae, Sang Hoon, et al.. (2017). Traffic Congestion Estimation by Adopting Recurrent Neural Network. The Journal of The Korea Institute of Intelligent Transport Systems. 16(6). 67–78. 2 indexed citations
3.
Bae, Sang Hoon, et al.. (2016). The Prospect and Barriers of Introduction of Institutional Research to Korea’s Universities. Asian Journal of Education. 17(2). 367–395. 1 indexed citations
4.
Bae, Sang Hoon, et al.. (2014). The Trend and Tasks of Meister High School Research: Network Text Analysis and Content Analysis. Korean Society for the Study of Vocational Education. 33(3). 83–104. 1 indexed citations
5.
Kim, Heung Cheol, Dae Young Yoon, Young Lan Seo, et al.. (2013). Incidental thyroid lesions identified by ultrasound in patients with non-thyroidal head and neck cancer. Acta Radiologica. 54(10). 1153–1158. 2 indexed citations
6.
Lee, Kwang Jae, et al.. (2010). A Case of Splenic Pseudoaneurysmal Rupture Misrecognized as Bleeding from Gastric Submucosal Tumor. Clinical Endoscopy. 40(6). 387–390.
7.
Yoon, Dae Young, Chan Hee Park, Suk Ki Chang, et al.. (2010). CT, MR, 18F-FDG PET/CT, and their combined use for the assessment of mandibular invasion by squamous cell carcinomas of the oral cavity. Acta Radiologica. 51(10). 1111–1119. 55 indexed citations
8.
Yoon, Dae Young, Suk Ki Chang, Kyoung Ja Lim, et al.. (2009). CT features of foreign body granulomas after cosmetic paraffin injection in the cervicofacial area. Diagnostic and Interventional Radiology. 16(2). 125–8. 15 indexed citations
9.
Bae, Young A, Hyun Beom Kim, Hee Sung Hwang, et al.. (2006). Cystic Adventitial Disease of the Popliteal Artery as Demonstrated by MDCT Angiography: A Case Report. Journal of the Korean Radiological Society. 54(4). 265–265. 1 indexed citations
10.
Koh, Sung Hye, et al.. (2004). Low-grade fibromyxoid sarcoma: ultrasound and magnetic resonance findings in two cases. Skeletal Radiology. 34(9). 550–554. 15 indexed citations
11.
Seo, Young Lan, et al.. (2002). Comparison of Quality of Ultrasonographic Image of the Pancreas: Tissue Harmonic Image vs. Fundamental Image. ULTRASONOGRAPHY. 21(3). 165–169.
12.
Seo, Young Lan, et al.. (2002). Doppler Sonography of Diabetic Feet: Quantitative Analysis of Blood Flow Volume. ULTRASONOGRAPHY. 21(3). 197–206.
13.
Kang, Yeonah, et al.. (2002). Comprehensive analysis of promoter methylation and altered expression of hMLH1 in gastric cancer cell lines with microsatellite instability. Journal of Cancer Research and Clinical Oncology. 128(3). 119–124. 18 indexed citations
14.
Choi, Chul Soon, et al.. (1998). Usefulness of the resistive index for the evaluation of transplanted kidneys. Transplantation Proceedings. 30(7). 3074–3075. 14 indexed citations
15.
Kim, Tae Kyoung, Joon Koo Han, Seojin Kim, Sang Hoon Bae, & Byung Ihn Choi. (1998). MR cholangiopancreatography: comparison between half-Fourier acquisition single-shot turbo spin-echo and two-dimensional turbo spin-echo pulse sequences. Abdominal Imaging. 23(4). 398–403. 11 indexed citations
16.
Kim, Do Kyun, Chul Soon Choi, Soo Young Chung, et al.. (1997). Comparison between Mammography and Ultrasonography for Palpable Breast Mass: Focusing Fibroadenoma and Breast Cancer. Journal of the Korean Radiological Society. 37(3). 561–561.
17.
Chung, Soo Young, et al.. (1996). Tuberculous Abscess in Retromammary Region: CT Findings. Journal of Computer Assisted Tomography. 20(5). 766–769. 17 indexed citations
18.
Chung, Soo Young, et al.. (1995). Breast tumors associated with nipple discharge correlation of findings on galactography and sonography. Clinical Imaging. 19(3). 165–171. 19 indexed citations
19.
Yi, Jeong Geun, et al.. (1993). Clival chordoma: CT and MR fidings. Journal of the Korean Radiological Society. 29(4). 687–687.
20.
Lim, Hyo Keun, et al.. (1992). Diagnosis of acute appendicitis in pregnant women: value of sonography.. American Journal of Roentgenology. 159(3). 539–542. 133 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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