Joo-Chang Kim

597 total citations
26 papers, 456 citations indexed

About

Joo-Chang Kim is a scholar working on Health Information Management, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Joo-Chang Kim has authored 26 papers receiving a total of 456 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Health Information Management, 15 papers in Information Systems and 7 papers in Computer Networks and Communications. Recurrent topics in Joo-Chang Kim's work include Innovation in Digital Healthcare Systems (18 papers), Technology and Data Analysis (13 papers) and Internet of Things and Social Network Interactions (5 papers). Joo-Chang Kim is often cited by papers focused on Innovation in Digital Healthcare Systems (18 papers), Technology and Data Analysis (13 papers) and Internet of Things and Social Network Interactions (5 papers). Joo-Chang Kim collaborates with scholars based in South Korea and Vietnam. Joo-Chang Kim's co-authors include Kyungyong Chung, Roy C. Park, Hoill Jung, Ji-Won Baek, Sungho Kim, Hyun Yoo and Kwang-Hoon Kim and has published in prestigious journals such as IEEE Access, Applied Sciences and Multimedia Tools and Applications.

In The Last Decade

Joo-Chang Kim

24 papers receiving 447 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Joo-Chang Kim South Korea 13 225 208 92 75 75 26 456
Hoill Jung South Korea 16 310 1.4× 291 1.4× 87 0.9× 150 2.0× 93 1.2× 32 597
Shujaat Hussain Pakistan 11 56 0.2× 142 0.7× 107 1.2× 193 2.6× 116 1.5× 37 492
Edward Rolando Núñez‐Valdéz Spain 13 71 0.3× 211 1.0× 157 1.7× 102 1.4× 73 1.0× 31 543
Malathi Devarajan India 13 52 0.2× 215 1.0× 170 1.8× 169 2.3× 99 1.3× 35 551
Thanveer Shaik Australia 10 64 0.3× 77 0.4× 248 2.7× 55 0.7× 48 0.6× 20 602
Md Ileas Pramanik Bangladesh 10 68 0.3× 77 0.4× 101 1.1× 104 1.4× 38 0.5× 17 433
Thi Ngoc Trang Tran Austria 12 31 0.1× 309 1.5× 266 2.9× 61 0.8× 65 0.9× 37 584
Punnarumol Temdee Thailand 13 63 0.3× 137 0.7× 131 1.4× 31 0.4× 56 0.7× 86 499
Abdulellah A. Alaboudi Saudi Arabia 8 27 0.1× 91 0.4× 69 0.8× 91 1.2× 23 0.3× 17 397
Kleinner Farias Brazil 11 77 0.3× 293 1.4× 158 1.7× 119 1.6× 27 0.4× 67 651

Countries citing papers authored by Joo-Chang Kim

Since Specialization
Citations

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

Fields of papers citing papers by Joo-Chang Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joo-Chang Kim. 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 Joo-Chang Kim. The network helps show where Joo-Chang Kim may publish in the future.

Co-authorship network of co-authors of Joo-Chang Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Joo-Chang Kim. A scholar is included among the top collaborators of Joo-Chang Kim 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 Joo-Chang Kim. Joo-Chang Kim 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, Joo-Chang, et al.. (2025). ViT-Core+: Lightweight Anomaly Detection Using Cut-Paste and Transformer-Based Feature Extractor. IEEE Access. 13. 177352–177365.
2.
Chung, Kyungyong, et al.. (2024). Extraction of Meta-Data for Recommendation Using Keyword Mapping. IEEE Access. 12. 103647–103659. 1 indexed citations
3.
Kim, Joo-Chang, et al.. (2024). Search and Recommendation Systems with Metadata Extensions. 38–42.
4.
Kim, Joo-Chang, et al.. (2024). Multi-Modal Deep Learning based Metadata Extensions for Video Clipping. International Journal on Advanced Science Engineering and Information Technology. 14(1). 375–380. 1 indexed citations
5.
Kim, Joo-Chang, et al.. (2023). A Deep Learning-Based Real-Time Video Object Contextualizing and Archiving System. 137–144. 2 indexed citations
6.
Kim, Joo-Chang & Kyungyong Chung. (2022). Recurrent Neural Network-Based Multimodal Deep Learning for Estimating Missing Values in Healthcare. Applied Sciences. 12(15). 7477–7477. 9 indexed citations
7.
Kim, Joo-Chang & Kyungyong Chung. (2020). Multi-Modal Stacked Denoising Autoencoder for Handling Missing Data in Healthcare Big Data. IEEE Access. 8. 104933–104943. 36 indexed citations
8.
Kim, Joo-Chang & Kyungyong Chung. (2020). Hybrid Multi-Modal Deep Learning using Collaborative Concat Layer in Health Bigdata. IEEE Access. 8. 192469–192480. 12 indexed citations
9.
Kim, Joo-Chang & Kyungyong Chung. (2020). Knowledge expansion of metadata using script mining analysis in multimedia recommendation. Multimedia Tools and Applications. 80(26-27). 34679–34695. 9 indexed citations
10.
Baek, Ji-Won, et al.. (2019). Hybrid clustering based health decision-making for improving dietary habits. Technology and Health Care. 27(5). 459–472. 35 indexed citations
11.
Kim, Joo-Chang & Kyungyong Chung. (2019). Prediction Model of User Physical Activity using Data Characteristics-based Long Short-term Memory Recurrent Neural Networks. KSII Transactions on Internet and Information Systems. 13(4). 40 indexed citations
12.
Kim, Joo-Chang & Kyungyong Chung. (2019). Discovery of knowledge of associative relations using opinion mining based on a health platform. Personal and Ubiquitous Computing. 24(5). 583–593. 7 indexed citations
13.
Kim, Joo-Chang, et al.. (2018). Sequence Mining based Manufacturing Process using Decision Model in Cognitive Factory. Journal of the Korean Chemical Society. 9(3). 53–59. 1 indexed citations
14.
Kim, Joo-Chang & Kyungyong Chung. (2018). Mining health-risk factors using PHR similarity in a hybrid P2P network. Peer-to-Peer Networking and Applications. 11(6). 1278–1287. 35 indexed citations
15.
Kim, Joo-Chang & Kyungyong Chung. (2018). Mining Based Time-Series Sleeping Pattern Analysis for Life Big-Data. Wireless Personal Communications. 105(2). 475–489. 20 indexed citations
16.
Kim, Joo-Chang & Kyungyong Chung. (2018). Neural-network based adaptive context prediction model for ambient intelligence. Journal of Ambient Intelligence and Humanized Computing. 11(4). 1451–1458. 37 indexed citations
17.
Kim, Joo-Chang, et al.. (2017). Mining based Mental Health and Blood Pressure Management Service for Smart Health. Journal of the Korea Convergence Society. 8(1). 13–18. 3 indexed citations
18.
Yoo, Hyun, et al.. (2017). Context aware based user customized light therapy service using security framework. Journal of Computer Virology and Hacking Techniques. 13(4). 279–288. 1 indexed citations
19.
Kim, Joo-Chang & Kyungyong Chung. (2016). Depression Index Service Using Knowledge Based Crowdsourcing in Smart Health. Wireless Personal Communications. 93(1). 255–268. 32 indexed citations
20.
Kim, Joo-Chang, Hoill Jung, Sungho Kim, & Kyungyong Chung. (2015). Slope Based Intelligent 3D Disaster Simulation Using Physics Engine. Wireless Personal Communications. 86(1). 183–199. 29 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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