Hyo Jung Hong

625 total citations · 1 hit paper
10 papers, 340 citations indexed

About

Hyo Jung Hong is a scholar working on Molecular Biology, Health Information Management and Health Informatics. According to data from OpenAlex, Hyo Jung Hong has authored 10 papers receiving a total of 340 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 2 papers in Health Information Management and 2 papers in Health Informatics. Recurrent topics in Hyo Jung Hong's work include Artificial Intelligence in Healthcare (2 papers), Artificial Intelligence in Healthcare and Education (2 papers) and Insect-Plant Interactions and Control (2 papers). Hyo Jung Hong is often cited by papers focused on Artificial Intelligence in Healthcare (2 papers), Artificial Intelligence in Healthcare and Education (2 papers) and Insect-Plant Interactions and Control (2 papers). Hyo Jung Hong collaborates with scholars based in South Korea, United States and Thailand. Hyo Jung Hong's co-authors include Nigam H. Shah, Nirav R. Shah, Akash Chaurasia, Oluwasanmi Koyejo, Suhana Bedi, Arnold Milstein, Jason Fries, Michael A. Pfeffer, Lisa Soleymani Lehmann and Dev Dash and has published in prestigious journals such as JAMA, Oncogene and International Journal of Molecular Sciences.

In The Last Decade

Hyo Jung Hong

9 papers receiving 330 citations

Hit Papers

Testing and Evaluation of Health Care Applications of Lar... 2024 2026 2025 2024 40 80 120

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hyo Jung Hong South Korea 7 116 87 64 57 43 10 340
Manuela Benary Germany 8 71 0.6× 89 1.0× 75 1.2× 32 0.6× 60 1.4× 16 245
Damian Rieke Germany 11 140 1.2× 90 1.0× 107 1.7× 95 1.7× 63 1.5× 42 402
Francesca Arezzo Italy 12 79 0.7× 29 0.3× 81 1.3× 145 2.5× 129 3.0× 65 514
Shoko Vos Netherlands 11 85 0.7× 26 0.3× 35 0.5× 63 1.1× 35 0.8× 24 311
Louis Cai United States 8 101 0.9× 86 1.0× 24 0.4× 90 1.6× 128 3.0× 26 404
Glynis Frans Belgium 12 76 0.7× 62 0.7× 32 0.5× 31 0.5× 45 1.0× 35 409
Michael Jonathan Kucharczyk Canada 11 39 0.3× 14 0.2× 53 0.8× 111 1.9× 324 7.5× 21 573
Rahul K. Arora Canada 8 103 0.9× 13 0.1× 15 0.2× 41 0.7× 13 0.3× 27 258
Elisabetta Xue Italy 9 26 0.2× 33 0.4× 36 0.6× 63 1.1× 20 0.5× 31 228
Tanja Jutzi Germany 6 32 0.3× 64 0.7× 121 1.9× 166 2.9× 123 2.9× 9 360

Countries citing papers authored by Hyo Jung Hong

Since Specialization
Citations

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

Fields of papers citing papers by Hyo Jung Hong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hyo Jung Hong. 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 Hyo Jung Hong. The network helps show where Hyo Jung Hong may publish in the future.

Co-authorship network of co-authors of Hyo Jung Hong

This figure shows the co-authorship network connecting the top 25 collaborators of Hyo Jung Hong. A scholar is included among the top collaborators of Hyo Jung Hong 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 Hyo Jung Hong. Hyo Jung Hong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

10 of 10 papers shown
2.
Bedi, Suhana, Dev Dash, Oluwasanmi Koyejo, et al.. (2024). A Systematic Review of Testing and Evaluation of Healthcare Applications of Large Language Models (LLMs). medRxiv. 16 indexed citations
3.
Bedi, Suhana, Dev Dash, Oluwasanmi Koyejo, et al.. (2024). Testing and Evaluation of Health Care Applications of Large Language Models. JAMA. 333(4). 319–319. 137 indexed citations breakdown →
4.
Khan, Murtaza, et al.. (2024). Plasticity in Gene Expression Patterns and CYPSF Gene Possibly Involved in the Etofenprox-Resistant Population of White-Backed Planthopper, Sogatella furcifera. International Journal of Molecular Sciences. 25(24). 13605–13605. 1 indexed citations
5.
Kim, Seokjoong, Harry C. Hwang, Jaemin Oh, et al.. (2016). Gene therapy using plasmid DNA-encoded anti-HER2 antibody for cancers that overexpress HER2. Cancer Gene Therapy. 23(10). 341–347. 16 indexed citations
6.
Song, In Ho, Tae Sup Lee, Hyo Jung Hong, et al.. (2016). Immuno-PET and activatable near-infrared fluorescence dual-modality imaging of L1-CAM expression in cholangiocarcinoma model.. 57. 1213–1213. 1 indexed citations
7.
Kim, Kyung‐Sup, et al.. (2008). Targeted gene therapy of LS174 T human colon carcinoma by anti-TAG-72 immunoliposomes. Cancer Gene Therapy. 15(5). 331–340. 15 indexed citations
8.
Jung, Haiyoung, Kwang‐Pyo Lee, Jung‐Hyun Park, et al.. (2007). TMPRSS4 promotes invasion, migration and metastasis of human tumor cells by facilitating an epithelial–mesenchymal transition. Oncogene. 27(18). 2635–2647. 127 indexed citations
9.
Jenkins, Edmund C., G. Y. Wen, Kwang Soo Kim, et al.. (1999). Prenatal fragile X detection using cytoplasmic and nuclear-specific monoclonal antibodies. American Journal of Medical Genetics. 83(4). 342–346. 7 indexed citations
10.
Ryu, Chun Jeih, et al.. (1997). Hepatitis B virus preS1 functions as a transcriptional activation domain.. Journal of General Virology. 78(5). 1083–1086. 20 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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