Seung‐Ho Shin

1.3k total citations
52 papers, 926 citations indexed

About

Seung‐Ho Shin is a scholar working on Cancer Research, Molecular Biology and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Seung‐Ho Shin has authored 52 papers receiving a total of 926 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Cancer Research, 12 papers in Molecular Biology and 11 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Seung‐Ho Shin's work include Cancer Genomics and Diagnostics (10 papers), Photorefractive and Nonlinear Optics (9 papers) and Advanced Optical Imaging Technologies (7 papers). Seung‐Ho Shin is often cited by papers focused on Cancer Genomics and Diagnostics (10 papers), Photorefractive and Nonlinear Optics (9 papers) and Advanced Optical Imaging Technologies (7 papers). Seung‐Ho Shin collaborates with scholars based in South Korea, United States and Italy. Seung‐Ho Shin's co-authors include Sun Shim Choi, Woong‐Yang Park, Donghyun Park, Bahram Javidi, Jae-Young Jang, Chang Eun Yoo, Yeon Jeong Kim, Yeji Kim, Shin‐Hyun Kim and Hui‐Sung Moon and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Immunity.

In The Last Decade

Seung‐Ho Shin

49 papers receiving 894 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Seung‐Ho Shin South Korea 16 271 208 135 116 115 52 926
Yi‐Shing Lisa Cheng United States 20 275 1.0× 114 0.5× 140 1.0× 34 0.3× 40 0.3× 56 1.2k
László Jakab Hungary 21 177 0.7× 39 0.2× 74 0.5× 16 0.1× 93 0.8× 82 1.3k
Simon Chen United States 15 177 0.7× 110 0.5× 97 0.7× 94 0.8× 9 0.1× 28 782
J Hayashi Japan 22 1.2k 4.4× 87 0.4× 49 0.4× 13 0.1× 60 0.5× 123 2.1k
Aditi Kanhere United Kingdom 18 1.0k 3.7× 246 1.2× 199 1.5× 15 0.1× 17 0.1× 38 1.6k
Yuan Jiang China 15 924 3.4× 99 0.5× 270 2.0× 12 0.1× 42 0.4× 54 1.6k
Kyung-Ah Kim South Korea 15 730 2.7× 35 0.2× 118 0.9× 26 0.2× 20 0.2× 48 1.1k
Feng He China 17 380 1.4× 48 0.2× 297 2.2× 19 0.2× 10 0.1× 58 1.0k
Jennifer E. Ward United States 16 521 1.9× 34 0.2× 134 1.0× 34 0.3× 60 0.5× 29 851
Raymond C. Chan United States 25 1.1k 4.0× 196 0.9× 84 0.6× 9 0.1× 21 0.2× 47 2.3k

Countries citing papers authored by Seung‐Ho Shin

Since Specialization
Citations

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

Fields of papers citing papers by Seung‐Ho Shin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Seung‐Ho Shin. 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 Seung‐Ho Shin. The network helps show where Seung‐Ho Shin may publish in the future.

Co-authorship network of co-authors of Seung‐Ho Shin

This figure shows the co-authorship network connecting the top 25 collaborators of Seung‐Ho Shin. A scholar is included among the top collaborators of Seung‐Ho Shin 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 Seung‐Ho Shin. Seung‐Ho Shin 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.
Kim, Hye-Jin, Seung‐Ho Shin, Chulho Kim, et al.. (2025). Machine Learning–Based Analysis of Lifestyle Risk Factors for Atherosclerotic Cardiovascular Disease: Retrospective Case-Control Study. JMIR Medical Informatics. 13. e74415–e74415. 1 indexed citations
2.
Yoon, Sang Eun, et al.. (2024). Feasibility of Circulating Tumor DNA Analysis in Patients with Follicular Lymphoma. Cancer Research and Treatment. 56(3). 920–935. 6 indexed citations
3.
Kang, Hyun‐Jung, et al.. (2024). Tuberculous Pleural Effusion-Derived Exosomal miR-130b-3p and miR-423-5p Promote the Proliferation of Lung Cancer Cells via Cyclin D1. International Journal of Molecular Sciences. 25(18). 10119–10119. 1 indexed citations
4.
Shin, Seung‐Ho, et al.. (2024). Natural Language Processing-Based Deep Learning to Predict the Loss of Consciousness Event Using Emergency Department Text Records. Applied Sciences. 14(23). 11399–11399. 1 indexed citations
5.
Kong, JungHo, Jin-Ho Kim, Donghyo Kim, et al.. (2023). Information about immune cell proportions and tumor stage improves the prediction of recurrence in patients with colorectal cancer. Patterns. 4(6). 100736–100736.
6.
Kim, Stephanie, Seung Cho Lee, Bumjin Lim, et al.. (2023). DNA methylation biomarkers distinguishing early-stage prostate cancer from benign prostatic hyperplasia. Prostate International. 11(2). 113–121. 12 indexed citations
7.
Menon, A Vipin, Yeon Jeong Kim, Junehawk Lee, et al.. (2022). Ultrafast prediction of somatic structural variations by filtering out reads matched to pan-genome k-mer sets. Nature Biomedical Engineering. 7(7). 853–866. 5 indexed citations
8.
Park, Gahee, Joo Kyung Park, Dae‐Soon Son, et al.. (2018). Utility of targeted deep sequencing for detecting circulating tumor DNA in pancreatic cancer patients. Scientific Reports. 8(1). 43 indexed citations
9.
Lee, Chung, Joon Seol Bae, Gyu Ha Ryu, et al.. (2017). A Method to Evaluate the Quality of Clinical Gene-Panel Sequencing Data for Single-Nucleotide Variant Detection. Journal of Molecular Diagnostics. 19(5). 651–658. 15 indexed citations
10.
Shin, Seung‐Ho, et al.. (2017). Transcriptome Analysis of Flowering Time Genes under Drought Stress in Maize Leaves. Frontiers in Plant Science. 8. 267–267. 57 indexed citations
11.
Yang, Jin‐Young, Min‐Soo Kim, Jae Hee Cheon, et al.. (2016). Enteric Viruses Ameliorate Gut Inflammation via Toll-like Receptor 3 and Toll-like Receptor 7-Mediated Interferon-β Production. Immunity. 44(4). 889–900. 156 indexed citations
12.
Kim, Kyung‐Hee, James Moon, Jae Yoon Kim, et al.. (2016). Evaluation of Maize Downy Mildew using Spreader Row Technique. Korean Journal of Crop Science. 61(1). 41–49. 5 indexed citations
13.
Lee, Hui‐Young, Seon‐Sook Han, Hwanseok Rhee, et al.. (2014). Differential expression of microRNAs and their target genes in non-small-cell lung cancer. Molecular Medicine Reports. 11(3). 2034–2040. 24 indexed citations
14.
Jang, Jae-Young, et al.. (2012). Depth extraction by using the correlation of the periodic function with an elemental image in integral imaging. Applied Optics. 51(16). 3279–3279. 28 indexed citations
15.
Jang, Jae-Young, et al.. (2011). Viewing angle enhanced integral imaging display by using a high refractive index medium. Applied Optics. 50(7). B71–B71. 37 indexed citations
16.
Shin, Seung‐Ho, et al.. (2009). Distortion correction of reconstructed three-dimensional image in an integral imaging system combined with a single imaging lens. Applied Optics. 48(17). 3108–3108. 5 indexed citations
17.
Kim, Chulho, et al.. (2002). Cervical Lymph Node Metastasis of Squamous Cell Carcinoma of the Oral Tongue and Floor of Mouth. Korean Journal of Otorhinolaryngology-head and Neck Surgery. 45(2). 154–158. 2 indexed citations
18.
Shin, Seung‐Ho. (2002). Proinflammatory cytokine profile in Vibrio vulnificus septicemic patients' sera. FEMS Immunology & Medical Microbiology. 33(2). 133–138. 2 indexed citations
19.
Shin, Seung‐Ho & Bahram Javidi. (2001). Three-dimensional object recognition by use of a photorefractive volume holographic processor. Optics Letters. 26(15). 1161–1161. 14 indexed citations
20.
Dou, Shuo‐Xing, et al.. (1998). Method for determining the two-beam coupling gain coefficients of photorefractive crystals. Optics Letters. 23(10). 753–753. 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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