Keun Ho Ryu

6.9k total citations
259 papers, 3.9k citations indexed

About

Keun Ho Ryu is a scholar working on Artificial Intelligence, Molecular Biology and Information Systems. According to data from OpenAlex, Keun Ho Ryu has authored 259 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 79 papers in Artificial Intelligence, 65 papers in Molecular Biology and 62 papers in Information Systems. Recurrent topics in Keun Ho Ryu's work include Data Mining Algorithms and Applications (47 papers), Data Management and Algorithms (40 papers) and Advanced Database Systems and Queries (20 papers). Keun Ho Ryu is often cited by papers focused on Data Mining Algorithms and Applications (47 papers), Data Management and Algorithms (40 papers) and Advanced Database Systems and Queries (20 papers). Keun Ho Ryu collaborates with scholars based in South Korea, Vietnam and China. Keun Ho Ryu's co-authors include Unil Yun, Yongjun Piao, Minghao Piao, Meijing Li, Erdenebileg Batbaatar, Tsendsuren Munkhdalai, Heungmo Ryang, Ho Sun Shon, Gangin Lee and Lkhagvadorj Munkhdalai and has published in prestigious journals such as Bioinformatics, PLoS ONE and The Journal of Physical Chemistry B.

In The Last Decade

Keun Ho Ryu

241 papers receiving 3.7k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Keun Ho Ryu South Korea	34	1.3k	980	739	560	421	259	3.9k
Charles X. Ling Canada	29	3.3k 2.6×	1.2k 1.2×	552 0.7×	665 1.2×	297 0.7×	131	5.7k
Dan Steinberg United States	8	1.8k 1.4×	886 0.9×	205 0.3×	216 0.4×	349 0.8×	15	4.3k
Amparo Alonso‐Betanzos Spain	34	2.7k 2.2×	494 0.5×	1.1k 1.5×	243 0.4×	404 1.0×	173	5.4k
Yong Hu China	33	1.3k 1.1×	449 0.5×	283 0.4×	520 0.9×	105 0.2×	119	4.5k
Mark A. Hall New Zealand	12	2.3k 1.8×	1.0k 1.1×	915 1.2×	412 0.7×	428 1.0×	15	4.8k
Manoranjan Dash Singapore	20	3.4k 2.7×	1.1k 1.1×	793 1.1×	921 1.6×	514 1.2×	68	5.8k
Jonathan M. Garibaldi United Kingdom	39	2.4k 1.9×	309 0.3×	1.0k 1.4×	411 0.7×	162 0.4×	274	6.5k
Juan J. Rodríguez Spain	25	1.8k 1.4×	330 0.3×	282 0.4×	170 0.3×	393 0.9×	76	3.3k
Stan Matwin Canada	36	4.3k 3.4×	1.3k 1.4×	436 0.6×	330 0.6×	607 1.4×	263	6.8k
Petra Perner Germany	19	2.0k 1.6×	1.6k 1.6×	284 0.4×	620 1.1×	663 1.6×	105	4.2k

Countries citing papers authored by Keun Ho Ryu

Since Specialization

Citations

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

Fields of papers citing papers by Keun Ho Ryu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Keun Ho Ryu. 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 Keun Ho Ryu. The network helps show where Keun Ho Ryu may publish in the future.

Co-authorship network of co-authors of Keun Ho Ryu

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Wang, Ling, et al.. (2023). EEG and ECG-Based Multi-Sensor Fusion Computing for Real-Time Fatigue Driving Recognition Based on Feedback Mechanism. Sensors. 23(20). 8386–8386. 12 indexed citations

Munkhdalai, Lkhagvadorj, et al.. (2023). NFT Appraisal Using Machine Learning. 160–166.

Munkhdalai, Lkhagvadorj, Tsendsuren Munkhdalai, Jang‐Eui Hong, et al.. (2023). Discrimination Neural Network Model for Binary Classification Tasks on Tabular Data. IEEE Access. 11. 15404–15418. 1 indexed citations

Munkhdalai, Lkhagvadorj, Tsendsuren Munkhdalai, Van-Huy Pham, et al.. (2022). Recurrent Neural Network-Augmented Locally Adaptive Interpretable Regression for Multivariate Time-Series Forecasting. IEEE Access. 10. 11871–11885. 11 indexed citations

Pham, Van-Huy, et al.. (2021). An Efficient Prediction Method for Coronary Heart Disease Risk Based on Two Deep Neural Networks Trained on Well-Ordered Training Datasets. IEEE Access. 9. 135210–135223. 31 indexed citations

Munkhdalai, Lkhagvadorj, Kwang Ho Park, Erdenebileg Batbaatar, Nipon Theera‐Umpon, & Keun Ho Ryu. (2020). Deep Learning-Based Demand Forecasting for Korean Postal Delivery Service. IEEE Access. 8. 188135–188145. 8 indexed citations

Munkhdalai, Lkhagvadorj, et al.. (2019). An Empirical Comparison of Machine-Learning Methods on Bank Client Credit Assessments. Sustainability. 11(3). 699–699. 77 indexed citations

Park, Kwang Ho, et al.. (2019). Reconstruction error based deep neural networks for coronary heart disease risk prediction. PLoS ONE. 14(12). e0225991–e0225991. 20 indexed citations

Kang, Ho Won, Young Joon Byun, Xuan‐Mei Piao, et al.. (2019). Methylation Signature for Prediction of Progression Free Survival in Surgically Treated Clear Cell Renal Cell Carcinoma. Journal of Korean Medical Science. 34(19). e144–e144. 17 indexed citations

10.

Yang, Eunjoo, et al.. (2018). A Simulation-Based Study on the Comparison of Statistical and Time Series Forecasting Methods for Early Detection of Infectious Disease Outbreaks. International Journal of Environmental Research and Public Health. 15(5). 966–966. 23 indexed citations

11.

Park, Hyun Woo, et al.. (2018). Global Research on Syndromic Surveillance from 1993 to 2017: Bibliometric Analysis and Visualization. Sustainability. 10(10). 3414–3414. 9 indexed citations

12.

Park, Hyun Woo, et al.. (2018). Positive Effect of Baby-Friendly Hospital Initiatives on Improving Mothers' Intention for Successful Breastfeeding in Korea. Journal of Korean Medical Science. 33(43). e272–e272. 15 indexed citations

13.

Kim, Sang Yeob, et al.. (2018). Statistical Analysis for Risk Factors and Prediction of Hypertension based on Health Behavior Information. Journal of Digital Contents Society. 19(4). 685–692. 1 indexed citations

14.

Ryu, Keun Ho, et al.. (2018). Prediction of Prehypertenison and Hypertension Based on Anthropometry, Blood Parameters, and Spirometry. International Journal of Environmental Research and Public Health. 15(11). 2571–2571. 21 indexed citations

15.

Ryu, Keun Ho, et al.. (2014). Clustering Analysis by Customer Feature based on SOM for Predicting Purchase Pattern in Recommendation System. Journal of the Korea Society of Computer and Information. 19(2). 193–200. 1 indexed citations

16.

Lee, Dong Gyu, et al.. (2010). Nested Ensemble Technique for Excellence Real Time Cardiac Health Monitoring.. 136. 519–525. 7 indexed citations

17.

Jung, Young–Jin, et al.. (2008). Air Pollution Monitoring System based on Geosensor Network. III – 1370. 58 indexed citations

18.

Ryu, Keun Ho, et al.. (2007). The Demand Survey and Correlational Analysis for Geological Data. Journal of the Korean Association of Geographic Information Studies. 10(1). 60–72. 1 indexed citations

19.

Lee, Bum Ju, et al.. (2006). Implementation of Subsequence Mapping Method for Sequential Pattern Mining. National Remote Sensing Bulletin. 22(5). 457–462. 1 indexed citations

20.

Kim, Dong Ho, et al.. (1996). The Spatiotemporal Relationship Operator. ITC-CSCC :International Technical Conference on Circuits Systems, Computers and Communications. 1035–1038. 3 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.

Explore authors with similar magnitude of impact