Sohi Bae

1.2k total citations
20 papers, 895 citations indexed

About

Sohi Bae is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Sohi Bae has authored 20 papers receiving a total of 895 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Radiology, Nuclear Medicine and Imaging, 6 papers in Genetics and 4 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Sohi Bae's work include Radiomics and Machine Learning in Medical Imaging (9 papers), Glioma Diagnosis and Treatment (6 papers) and MRI in cancer diagnosis (4 papers). Sohi Bae is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (9 papers), Glioma Diagnosis and Treatment (6 papers) and MRI in cancer diagnosis (4 papers). Sohi Bae collaborates with scholars based in South Korea, United States and Russia. Sohi Bae's co-authors include Seung‐Koo Lee, Sung Soo Ahn, Se Hoon Kim, Jong Hee Chang, Seok‐Gu Kang, Yoon Seong Choi, Eui Hyun Kim, Kyunghwa Han, Jinna Kim and Seung Hong Choi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Radiology.

In The Last Decade

Sohi Bae

18 papers receiving 889 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sohi Bae South Korea 11 681 489 184 121 109 20 895
Yoon Seong Choi South Korea 22 1.2k 1.8× 748 1.5× 242 1.3× 108 0.9× 134 1.2× 42 1.7k
Jay Patel United States 15 447 0.7× 205 0.4× 179 1.0× 46 0.4× 115 1.1× 31 725
James R. Fink United States 20 556 0.8× 442 0.9× 261 1.4× 56 0.5× 103 0.9× 37 1.1k
Zenghui Qian China 18 672 1.0× 583 1.2× 481 2.6× 105 0.9× 109 1.0× 54 1.4k
Archya Dasgupta India 15 306 0.4× 259 0.5× 160 0.9× 37 0.3× 94 0.9× 75 615
Hwan-ho Cho South Korea 15 683 1.0× 174 0.4× 219 1.2× 97 0.8× 122 1.1× 29 819
Maarten M.J. Wijnenga Netherlands 11 436 0.6× 683 1.4× 194 1.1× 95 0.8× 36 0.3× 21 818
Anahita Fathi Kazerooni United States 16 396 0.6× 209 0.4× 58 0.3× 85 0.7× 84 0.8× 65 606
Shuaitong Zhang China 12 487 0.7× 279 0.6× 185 1.0× 36 0.3× 60 0.6× 24 617
Jan‐Michael Werner Germany 17 428 0.6× 488 1.0× 211 1.1× 36 0.3× 47 0.4× 58 779

Countries citing papers authored by Sohi Bae

Since Specialization
Citations

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

Fields of papers citing papers by Sohi Bae

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sohi Bae

This figure shows the co-authorship network connecting the top 25 collaborators of Sohi Bae. A scholar is included among the top collaborators of Sohi 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 Sohi Bae. Sohi 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, Sohi, et al.. (2022). A Case of Nasal Septum Gossypiboma 14 Years After Septorhinoplasty. SHILAP Revista de lepidopterología. 29(2). 101–105.
2.
Kim, Hwiyoung, Sung Soo Ahn, Beomseok Sohn, et al.. (2021). Development and Validation of a Deep Learning–Based Model to Distinguish Glioblastoma from Solitary Brain Metastasis Using Conventional MR Images. American Journal of Neuroradiology. 42(5). 838–844. 42 indexed citations
3.
Bae, Sohi, Chansik An, Sung Soo Ahn, et al.. (2020). Robust performance of deep learning for distinguishing glioblastoma from single brain metastasis using radiomic features: model development and validation. Scientific Reports. 10(1). 12110–12110. 78 indexed citations
4.
Bae, Sohi, Sung Soo Ahn, Byung Moon Kim, et al.. (2020). Hyperattenuating lesions after mechanical thrombectomy in acute ischaemic stroke: factors predicting symptomatic haemorrhage and clinical outcomes. Clinical Radiology. 76(1). 80.e15–80.e23. 5 indexed citations
5.
Joo, Bio, Sung Soo Ahn, Pyeong Ho Yoon, et al.. (2020). A deep learning algorithm may automate intracranial aneurysm detection on MR angiography with high diagnostic performance. European Radiology. 30(11). 5785–5793. 61 indexed citations
6.
Bae, Sohi, Yoon Seong Choi, Beomseok Sohn, et al.. (2020). Squamous Cell Carcinoma and Lymphoma of the Oropharynx: Differentiation Using a Radiomics Approach. Yonsei Medical Journal. 61(10). 895–895. 8 indexed citations
7.
Choi, Yoon Seong, Sohi Bae, Jong Hee Chang, et al.. (2020). Fully automated hybrid approach to predict theIDHmutation status of gliomas via deep learning and radiomics. Neuro-Oncology. 23(2). 304–313. 174 indexed citations
8.
Bae, Sohi, et al.. (2020). Isolated Unilateral Ptosis Caused by Idiopathic Orbital Myositis. 12(2). 39–43.
9.
Lee, Minsu, Kyunghwa Han, Sung Soo Ahn, et al.. (2019). The added prognostic value of radiological phenotype combined with clinical features and molecular subtype in anaplastic gliomas. Journal of Neuro-Oncology. 142(1). 129–138. 12 indexed citations
10.
Suh, Hie Bum, Sohi Bae, Sung Soo Ahn, et al.. (2018). Primary central nervous system lymphoma and atypical glioblastoma: Differentiation using radiomics approach. European Radiology. 28(9). 3832–3839. 107 indexed citations
11.
Bae, Sohi, Yoon Seong Choi, Sung Soo Ahn, et al.. (2018). Radiomic MRI Phenotyping of Glioblastoma: Improving Survival Prediction. Radiology. 289(3). 797–806. 176 indexed citations
12.
Bae, Sohi, Ho‐Joon Lee, Woong Nam, et al.. (2018). MR lymphography for sentinel lymph node detection in patients with oral cavity cancer: Preliminary clinical study. Head & Neck. 40(7). 1483–1488. 9 indexed citations
14.
Park, Yae Won, Kyunghwa Han, Sung Soo Ahn, et al.. (2017). Prediction ofIDH1-Mutation and 1p/19q-Codeletion Status Using Preoperative MR Imaging Phenotypes in Lower Grade Gliomas. American Journal of Neuroradiology. 39(1). 37–42. 119 indexed citations
15.
Bae, Sohi, Sung Soo Ahn, Jong Hee Chang, & Se Hoon Kim. (2017). Intra-Suprasellar Schwannoma Presumably Originating from the Internal Carotid Artery Wall. Clinical Neuroradiology. 28(1). 127–135. 2 indexed citations
16.
Bae, Sohi, Ho‐Joon Lee, Kyunghwa Han, et al.. (2017). Gadolinium deposition in the brain: association with various GBCAs using a generalized additive model. European Radiology. 27(8). 3353–3361. 29 indexed citations
17.
Bae, Sohi, Man Deuk Kim, Gyoung Min Kim, et al.. (2015). Uterine Artery Embolization for Adenomyosis: Percentage of Necrosis Predicts Midterm Clinical Recurrence. Journal of Vascular and Interventional Radiology. 26(9). 1290–1296.e2. 27 indexed citations
18.
Bae, Sohi, Jung Hyun Yoon, Hee Jung Moon, Min Jung Kim, & Eun‐Kyung Kim. (2015). Breast Microcalcifications: Diagnostic Outcomes According to Image-Guided Biopsy Method. Korean Journal of Radiology. 16(5). 996–996. 29 indexed citations
19.
Bae, Sohi, Myung‐Joon Kim, Choon-Sik Yoon, et al.. (2014). Effects of adaptive statistical iterative reconstruction on radiation dose reduction and diagnostic accuracy of pediatric abdominal CT. Pediatric Radiology. 44(12). 1541–1547. 7 indexed citations
20.
Jang, Tae Jung, et al.. (1997). Decreased gastric proliferation of foveolar epithelial cells after the eradication of Helicobacter pylori. Journal of Korean Medical Science. 12(5). 421–421. 1 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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