Youngdoo Son
Impact in
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- Artificial Intelligence in Healthcare
- Artificial Intelligence top 5%
- Anomaly Detection Techniques and Applications
- AI in cancer detection
Papers in
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- Anomaly Detection Techniques and Applications 9
- Machine Learning and Data Classification 4
- Neural Networks and Applications 4
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- Face and Expression Recognition 4
- Co-authors
- Muhammad Fazal Ijaz (3 shared papers)Muhammad Attique (1 shared paper)Jaewook Lee (8 shared papers)Wonjoon Kim (6 shared papers)Yung-Seop Lee (1 shared paper)Sangho Lee (9 shared papers)Sekyoung Youm (2 shared papers)Myong K. Jeong (4 shared papers)
- Journals
- Scientific Reports (5 papers)Expert Systems with Applications (4 papers)Applied Sciences (4 papers)Information Sciences (3 papers)IEEE Access (3 papers)
- Partner nations
- South KoreaUnited StatesIndia
In The Last Decade
Youngdoo Son
45 papers receiving 806 citations
Peers
Comparison fields: 5 of 146
- Health Information Management 54
- Artificial Intelligence 309
- Health Informatics 13
- Oral Surgery 55
- Computer Vision and Pattern Recognition 127
Countries citing papers authored by Youngdoo Son
This map shows the geographic impact of Youngdoo Son'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 Youngdoo Son with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Youngdoo Son more than expected).
Fields of papers citing papers by Youngdoo Son
This network shows the impact of papers produced by Youngdoo Son. 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 Youngdoo Son. The network helps show where Youngdoo Son may publish in the future.
Co-authors
The 25 scholars most cited alongside Youngdoo Son, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 199 | |
| 2 | 2021 | 68 | |
| 3 | 2021 | 65 | |
| 4 | 2022 | 49 | |
| 5 | 2018 | 47 | |
| 6 | 2019 | 44 | |
| 7 | 2020 | 43 | |
| 8 | 2024 | 35 | |
| 9 | 2016 | 27 | |
| 10 | 2012 | 26 | |
| 11 | 2020 | 21 | |
| 12 | 2022 | 20 | |
| 13 | 2021 | 18 | |
| 14 | 2023 | 15 | |
| 15 | 2019 | 14 | |
| 16 | 2014 | 14 | |
| 17 | 2016 | 13 | |
| 18 | 2016 | 12 | |
| 19 | 2021 | 8 | |
| 20 | 2017 | 8 |
About Youngdoo Son
Youngdoo Son is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Biomedical Engineering and Signal Processing, having authored 47 papers that have together received 842 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (9 papers), Face and Expression Recognition (4 papers), Time Series Analysis and Forecasting (4 papers), Advanced Photocatalysis Techniques (4 papers), Machine Learning and Data Classification (4 papers), Neural Networks and Applications (4 papers), Industrial Vision Systems and Defect Detection (3 papers) and Stock Market Forecasting Methods (3 papers). The work is most often cited by research in Health Information Management (54 citations), Artificial Intelligence (309 citations), Health Informatics (13 citations), Oral Surgery (55 citations) and Computer Vision and Pattern Recognition (127 citations). Youngdoo Son has collaborated with scholars based in South Korea, United States and India. Frequent co-authors include Muhammad Fazal Ijaz, Muhammad Attique, Jaewook Lee, Wonjoon Kim, Yung-Seop Lee, Sangho Lee, Sekyoung Youm, Myong K. Jeong, Yogesh Kumar and Shashi Bhushan. Their work appears in journals such as Scientific Reports, Expert Systems with Applications, Applied Sciences, Information Sciences and IEEE Access.
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.