Jin‐Hyoung Cho

1.1k total citations
53 papers, 847 citations indexed

About

Jin‐Hyoung Cho is a scholar working on Orthodontics, Oral Surgery and Molecular Biology. According to data from OpenAlex, Jin‐Hyoung Cho has authored 53 papers receiving a total of 847 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Orthodontics, 32 papers in Oral Surgery and 11 papers in Molecular Biology. Recurrent topics in Jin‐Hyoung Cho's work include Orthodontics and Dentofacial Orthopedics (30 papers), Dental Radiography and Imaging (28 papers) and Temporomandibular Joint Disorders (10 papers). Jin‐Hyoung Cho is often cited by papers focused on Orthodontics and Dentofacial Orthopedics (30 papers), Dental Radiography and Imaging (28 papers) and Temporomandibular Joint Disorders (10 papers). Jin‐Hyoung Cho collaborates with scholars based in South Korea, United States and Russia. Jin‐Hyoung Cho's co-authors include Hyeon‐Shik Hwang, Ki‐Heon Lee, Kyung-Min Lee, Won Joon Lee, Hoi‐Jeong Lim, Caroline Wilkinson, Seung‐Hak Baek, Chaeyong Jung, Jeong‐Tae Koh and Mihee Hong and has published in prestigious journals such as Nature Communications, PLoS ONE and Scientific Reports.

In The Last Decade

Jin‐Hyoung Cho

50 papers receiving 829 citations

Peers

Jin‐Hyoung Cho
Kyung-Min Lee South Korea
Mazyar Moshiri United States
Hyoung-Seon Baik South Korea
Aditya Tadinada United States
Insan Jang South Korea
Marília Yatabe United States
Kyung-Min Lee South Korea
Jin‐Hyoung Cho
Citations per year, relative to Jin‐Hyoung Cho Jin‐Hyoung Cho (= 1×) peers Kyung-Min Lee

Countries citing papers authored by Jin‐Hyoung Cho

Since Specialization
Citations

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

Fields of papers citing papers by Jin‐Hyoung Cho

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jin‐Hyoung Cho. 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 Jin‐Hyoung Cho. The network helps show where Jin‐Hyoung Cho may publish in the future.

Co-authorship network of co-authors of Jin‐Hyoung Cho

This figure shows the co-authorship network connecting the top 25 collaborators of Jin‐Hyoung Cho. A scholar is included among the top collaborators of Jin‐Hyoung Cho 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 Jin‐Hyoung Cho. Jin‐Hyoung Cho 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, In-Hwan, Jun‐Sik Kim, Jin‐Hyoung Cho, et al.. (2025). Predicting orthognathic surgery results as postoperative lateral cephalograms using graph neural networks and diffusion models. Nature Communications. 16(1). 2586–2586. 2 indexed citations
2.
Kim, In-Hwan, Jin‐Hyoung Cho, Kyung‐Hwa Kang, et al.. (2025). Accuracy of artificial intelligence-assisted soft tissue landmark identification in serial lateral cephalograms of Class III two-jaw surgery patients. The Korean Journal of Orthodontics. 55(5). 392–404.
3.
Zhang, Meiling, et al.. (2024). Evaluation of Aligners and Root Resorption: An Overview of Systematic Reviews. Journal of Clinical Medicine. 13(7). 1950–1950. 3 indexed citations
4.
Kim, Jun‐Sik, Jin‐Hyoung Cho, Mihee Hong, et al.. (2023). Accuracy of posteroanterior cephalogram landmarks and measurements identification using a cascaded convolutional neural network algorithm: A multicenter study. The Korean Journal of Orthodontics. 54(1). 48–58. 1 indexed citations
5.
Kim, In-Hwan, Jun‐Sik Kim, Jaewoo Park, et al.. (2023). Orthognathic surgical planning using graph CNN with dual embedding module: External validations with multi-hospital datasets. Computer Methods and Programs in Biomedicine. 242. 107853–107853. 5 indexed citations
6.
Kim, Young Ho, In-Hwan Kim, Yoon‐Ji Kim, et al.. (2023). The prediction of sagittal chin point relapse following two-jaw surgery using machine learning. Scientific Reports. 13(1). 6 indexed citations
7.
Kim, Minseok, et al.. (2023). Three-dimensional evaluation of the association between tongue position and upper airway morphology in adults: A cross-sectional study. The Korean Journal of Orthodontics. 53(5). 317–327. 2 indexed citations
8.
Kim, In-Hwan, Jin‐Hyoung Cho, Mihee Hong, et al.. (2022). Accuracy of auto-identification of the posteroanterior cephalometric landmarks using cascade convolution neural network algorithm and cephalometric images of different quality from nationwide multiple centers. American Journal of Orthodontics and Dentofacial Orthopedics. 161(4). e361–e371. 13 indexed citations
9.
Oh, Hee-Kyun, et al.. (2022). Comparison of short-term condylar positional changes in mandibular prognathism after surgery-first approach: Symmetric setback versus asymmetric setback. Journal of Stomatology Oral and Maxillofacial Surgery. 123(6). e940–e947. 1 indexed citations
10.
Hong, Mihee, In-Hwan Kim, Jin‐Hyoung Cho, et al.. (2022). Accuracy of artificial intelligence-assisted landmark identification in serial lateral cephalograms of Class III patients who underwent orthodontic treatment and two-jaw orthognathic surgery. The Korean Journal of Orthodontics. 52(4). 287–297. 22 indexed citations
11.
Lee, Bin-Na, et al.. (2022). Periodontal ligament preloading and rapid prototyping of the donor tooth in the autotransplantation of premolars with complete root formation. American Journal of Orthodontics and Dentofacial Orthopedics. 162(1). 108–121. 1 indexed citations
12.
Kim, Ki‐Hyun, et al.. (2021). Infrared Clinical Enamel Crack Detector Based on Silicon CCD and Its Application: A High-Quality and Low-Cost Option. Journal of Imaging. 7(12). 259–259. 4 indexed citations
13.
Kim, In-Hwan, Yoon‐Ji Kim, Minji Kim, et al.. (2021). Accuracy of automated identification of lateral cephalometric landmarks using cascade convolutional neural networks on lateral cephalograms from nationwide multi‐centres. Orthodontics and Craniofacial Research. 24(S2). 59–67. 43 indexed citations
14.
Cho, Jin‐Hyoung, et al.. (2016). Dimensional accuracy of digital dental models from cone-beam computed tomography scans of alginate impressions according to time elapsed after the impressions. American Journal of Orthodontics and Dentofacial Orthopedics. 149(2). 287–294. 14 indexed citations
15.
16.
Lee, Kyung-Min, Won Joon Lee, Jin‐Hyoung Cho, & Hyeon‐Shik Hwang. (2014). Three-dimensional prediction of the nose for facial reconstruction using cone-beam computed tomography. Forensic Science International. 236. 194.e1–194.e5. 40 indexed citations
17.
Kook, Min-Suk, Seunggon Jung, Hong-Ju Park, et al.. (2013). A comparison study of different facial soft tissue analysis methods. Journal of Cranio-Maxillofacial Surgery. 42(5). 648–656. 47 indexed citations
18.
Cho, Jin‐Hyoung, et al.. (2011). Registration accuracy in the integration of laser-scanned dental images into maxillofacial cone-beam computed tomography images. American Journal of Orthodontics and Dentofacial Orthopedics. 140(4). 585–591. 72 indexed citations
19.
Cho, Jin‐Hyoung, et al.. (2009). VALIDITY OF SUPERIMPOSITION RANGE AT 3-DIMENSIONAL FACIAL IMAGES. Maxillofacial Plastic and Reconstructive Surgery. 31(2). 149–157. 2 indexed citations
20.
Cho, Jin‐Hyoung, Eun-Jung Kim, Byeong C. Kim, et al.. (2007). Correlations of frontal lip-line canting with craniofacial morphology and muscular activity. American Journal of Orthodontics and Dentofacial Orthopedics. 132(3). 278.e7–278.e14. 26 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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