Youngdoo Son
Impact in
-
- Artificial Intelligence in Healthcare
- Health Informatics top 10%
Papers in
-
- Anomaly Detection Techniques and Applications 10
- Neural Networks and Applications 4
- Machine Learning and Data Classification 4
- Domain Adaptation and Few-Shot Learning 3
-
- 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 (11 shared papers)Sekyoung Youm (2 shared papers)Myong K. Jeong (4 shared papers)
- Journals
- Scientific Reports (5 papers)Applied Sciences (4 papers)Expert Systems with Applications (4 papers)Information Sciences (4 papers)IEEE Access (3 papers)
- Partner nations
- South KoreaUnited StatesIndia
In The Last Decade
Youngdoo Son
47 papers receiving 912 citations
Youngdoo Son's Hit Papers
Peers
Comparison fields: 5 of 144
- Health Information Management 58
- Health Informatics 13
- Artificial Intelligence 326
- Oral Surgery 54
- Computer Vision and Pattern Recognition 132
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 51 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Data-Driven Cervical Cancer Prediction Model with Outlier Detection and Over-Sampling Methods Hit paper breakdown → | 2020 | 215 |
| 2 | 2021 | 76 | |
| 3 | 2021 | 67 | |
| 4 | 2022 | 54 | |
| 5 | 2018 | 53 | |
| 6 | 2024 | 52 | |
| 7 | 2019 | 49 | |
| 8 | 2020 | 44 | |
| 9 | 2016 | 31 | |
| 10 | 2012 | 27 | |
| 11 | 2022 | 26 | |
| 12 | 2020 | 23 | |
| 13 | 2021 | 19 | |
| 14 | 2019 | 16 | |
| 15 | 2023 | 15 | |
| 16 | 2014 | 15 | |
| 17 | 2016 | 14 | |
| 18 | 2016 | 12 | |
| 19 | 2023 | 11 | |
| 20 | 2021 | 10 |
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 51 papers that have together received 944 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (10 papers), Time Series Analysis and Forecasting (5 papers), Advanced Photocatalysis Techniques (4 papers), Face and Expression Recognition (4 papers), Neural Networks and Applications (4 papers), Machine Learning and Data Classification (4 papers), Domain Adaptation and Few-Shot Learning (3 papers) and Stock Market Forecasting Methods (3 papers). The work is most often cited by research in Health Information Management (58 citations), Health Informatics (13 citations), Artificial Intelligence (326 citations), Oral Surgery (54 citations) and Computer Vision and Pattern Recognition (132 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 Myung Hwan Yun. Their work appears in journals such as Scientific Reports, Applied Sciences, Expert Systems with Applications, 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.