Yoo Sung Song

1.3k total citations
54 papers, 875 citations indexed

About

Yoo Sung Song is a scholar working on Neurology, Cellular and Molecular Neuroscience and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Yoo Sung Song has authored 54 papers receiving a total of 875 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Neurology, 16 papers in Cellular and Molecular Neuroscience and 15 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Yoo Sung Song's work include Parkinson's Disease Mechanisms and Treatments (19 papers), Neurological disorders and treatments (18 papers) and Neuroscience and Neuropharmacology Research (6 papers). Yoo Sung Song is often cited by papers focused on Parkinson's Disease Mechanisms and Treatments (19 papers), Neurological disorders and treatments (18 papers) and Neuroscience and Neuropharmacology Research (6 papers). Yoo Sung Song collaborates with scholars based in South Korea, United States and Ethiopia. Yoo Sung Song's co-authors include Jong‐Min Kim, Yun Jung Bae, Won Woo Lee, Sang Eun Kim, Byung Se Choi, Se Jin Cho, Jae Hyoung Kim, Yoonho Nam, Byung Chul Lee and Nayoung Ryoo and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Yoo Sung Song

52 papers receiving 870 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yoo Sung Song South Korea 16 330 252 226 134 82 54 875
Xiaopei Xu China 17 163 0.5× 245 1.0× 178 0.8× 161 1.2× 61 0.7× 80 811
Judith de Vos Netherlands 17 214 0.6× 323 1.3× 94 0.4× 110 0.8× 99 1.2× 38 762
Xiaoli Si China 17 287 0.9× 345 1.4× 113 0.5× 198 1.5× 37 0.5× 34 788
Hisato Ishii Japan 14 235 0.7× 222 0.9× 73 0.3× 107 0.8× 56 0.7× 110 771
Thomas Reithmeier Germany 19 478 1.4× 239 0.9× 218 1.0× 268 2.0× 150 1.8× 36 1.4k
Joachim Brumberg Germany 16 565 1.7× 304 1.2× 130 0.6× 110 0.8× 66 0.8× 47 889
Yafell Serulle United States 15 325 1.0× 313 1.2× 68 0.3× 164 1.2× 70 0.9× 43 708
Seong Ho Jeong South Korea 15 282 0.9× 153 0.6× 94 0.4× 166 1.2× 167 2.0× 59 797
Denis E. Bragin United States 19 261 0.8× 272 1.1× 159 0.7× 252 1.9× 108 1.3× 80 981
Domenico La Torre Italy 23 313 0.9× 221 0.9× 114 0.5× 387 2.9× 73 0.9× 67 1.5k

Countries citing papers authored by Yoo Sung Song

Since Specialization
Citations

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

Fields of papers citing papers by Yoo Sung Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yoo Sung Song. 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 Yoo Sung Song. The network helps show where Yoo Sung Song may publish in the future.

Co-authorship network of co-authors of Yoo Sung Song

This figure shows the co-authorship network connecting the top 25 collaborators of Yoo Sung Song. A scholar is included among the top collaborators of Yoo Sung Song 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 Yoo Sung Song. Yoo Sung Song 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.
Wang, Xubo, et al.. (2025). Emerging Plant-Derived Exosome-Like Particles Reveal Key Therapeutic Benefits. A Comprehensive Review of Evidence. International Journal of Nanomedicine. Volume 20. 12393–12411. 1 indexed citations
2.
Jeong, Eun Hye, Jae Yong Lee, & Yoo Sung Song. (2025). Longitudinal Serotonergic and Dopaminergic Binding: Impact on Parkinson's Disease Progression and Levodopa Dyskinesia. Journal of Neuroimaging. 35(1). e70014–e70014. 1 indexed citations
3.
4.
Bang, Ji-In, Won‐Woo Lee, Sang‐Geon Cho, Miyoung Choi, & Yoo Sung Song. (2024). The Diagnostic Accuracy of SPECT Imaging in Patients With Suspected Pulmonary Embolism. Clinical Nuclear Medicine. 49(7). 637–643. 2 indexed citations
5.
6.
Bae, Yun Jung, Jong‐Min Kim, Byung Se Choi, et al.. (2023). Altered Brain Glymphatic Flow at Diffusion-Tensor MRI in Rapid Eye Movement Sleep Behavior Disorder. Radiology. 307(5). e221848–e221848. 72 indexed citations
7.
Lee, Won Woo, Yoo Sung Song, & Young So. (2023). Quantitative Iodine-123 single-photon emission computed tomography/computed tomography for Iodine-131 therapy of an autonomously functioning thyroid nodule. SHILAP Revista de lepidopterología. 7(1). 4–4. 3 indexed citations
8.
Bae, Yun Jung, Jong‐Min Kim, Jong‐Min Kim, et al.. (2023). Glymphatic function assessment in Parkinson's disease using diffusion tensor image analysis along the perivascular space. Parkinsonism & Related Disorders. 114. 105767–105767. 47 indexed citations
9.
10.
Jeong, Eun Hye, et al.. (2022). Serial changes of I-123 FP-CIT SPECT binding asymmetry in Parkinson's disease: Analysis of the PPMI data. Frontiers in Neurology. 13. 976101–976101. 4 indexed citations
11.
Bae, Yun Jung, Yoo Sung Song, Byung Se Choi, et al.. (2020). Comparison of susceptibility-weighted imaging and susceptibility map-weighted imaging for the diagnosis of Parkinsonism with nigral hyperintensity. European Journal of Radiology. 134. 109398–109398. 9 indexed citations
12.
Bae, Sungwoo, Yusuhn Kang, Yoo Sung Song, & Won‐Woo Lee. (2019). Maximum standardized uptake value of foot SPECT/CT using Tc-99m HDP in patients with accessory navicular bone as a predictor of surgical treatment. Medicine. 98(2). e14022–e14022. 24 indexed citations
13.
Clayman, Gary L., Ian D. Hay, Mimi I. Hu, et al.. (2018). 88 th Annual Meeting of the American Thyroid Association. Thyroid. 28(S1). P–1. 6 indexed citations
14.
Kim, Ji-Hyun, Hyun‐Jong Lee, Ji-In Bang, et al.. (2018). Quantitative Single-Photon Emission Computed Tomography/Computed Tomography for Evaluation of Salivary Gland Dysfunction in Sjögren’s Syndrome Patients. Nuclear Medicine and Molecular Imaging. 52(5). 368–376. 14 indexed citations
15.
Song, Yoo Sung, et al.. (2017). Imaging of Integrin α v β 3 Expression in Lung Cancers and Brain Tumors Using Single-Photon Emission Computed Tomography with a Novel Radiotracer 99m Tc-IDA-D-[c(RGDfK)] 2. Cancer Biotherapy and Radiopharmaceuticals. 32(8). 288–296. 10 indexed citations
16.
Song, Yoo Sung, et al.. (2017). Serum Ceruloplasmin and Striatal Dopamine Transporter Density in Parkinson Disease. Clinical Nuclear Medicine. 42(9). 675–679. 5 indexed citations
17.
Kim, Ji‐Hyun, Yoo Sung Song, Jong Seok Lee, Won Woo Lee, & Sang Eun Kim. (2017). Risk stratification of diffuse large B-cell lymphoma with interim PET-CT based on different cutoff Deauville scores. Leukemia & lymphoma. 59(2). 340–347. 24 indexed citations
18.
Song, Yoo Sung, Won Woo Lee, Jong Seok Lee, & Sang Eun Kim. (2015). Prediction of Central Nervous System Relapse of Diffuse Large B-Cell Lymphoma Using Pretherapeutic [18F]2-Fluoro-2-Deoxyglucose (FDG) Positron Emission Tomography/Computed Tomography. Medicine. 94(44). e1978–e1978. 10 indexed citations
19.
20.
Song, Yoo Sung, Won‐Woo Lee, Jin-Haeng Chung, et al.. (2008). Correlation between FDG uptake and glucose transporter type 1 expression in neuroendocrine tumors of the lung. Lung Cancer. 61(1). 54–60. 41 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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