Sanghoon Lee
Impact in
- Health Informatics top 10%
- Biophysics top 5%
- Cell Image Analysis Techniques
Papers in
-
- AI in cancer detection 10
- Topic Modeling 4
- Speech Recognition and Synthesis 4
- Semantic Web and Ontologies 3
-
- Medical Image Segmentation Techniques 4
- Co-authors
- Lee Cooper (5 shared papers)David A. Gutman (5 shared papers)Jonathan Beezley (2 shared papers)David Manthey (2 shared papers)Seong–Whan Lee (5 shared papers)Deepak R. Chittajallu (2 shared papers)Mohammed Khalilia (1 shared paper)Mohamed Amgad (3 shared papers)
- Journals
- Cancer Research (2 papers)Scientific Reports (2 papers)iScience (1 paper)Journal of Biomedical Informatics (1 paper)Gynecologic Oncology (1 paper)
- Partner nations
- United StatesSouth KoreaPhilippines
In The Last Decade
Sanghoon Lee
41 papers receiving 405 citations
Peers
Comparison fields: 5 of 103
- Health Informatics 12
- Biophysics 50
- Artificial Intelligence 210
- Signal Processing 43
- Computer Vision and Pattern Recognition 79
Countries citing papers authored by Sanghoon Lee
This map shows the geographic impact of Sanghoon Lee'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 Sanghoon Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sanghoon Lee more than expected).
Fields of papers citing papers by Sanghoon Lee
This network shows the impact of papers produced by Sanghoon Lee. 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 Sanghoon Lee. The network helps show where Sanghoon Lee may publish in the future.
Co-authors
The 25 scholars most cited alongside Sanghoon Lee, 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 46 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 103 | |
| 2 | 2017 | 48 | |
| 3 | 2021 | 32 | |
| 4 | 2019 | 31 | |
| 5 | 2021 | 20 | |
| 6 | 2022 | 17 | |
| 7 | 2020 | 14 | |
| 8 | 2016 | 14 | |
| 9 | 2019 | 13 | |
| 10 | 2016 | 11 | |
| 11 | 2021 | 8 | |
| 12 | 2024 | 8 | |
| 13 | 2022 | 7 | |
| 14 | 2021 | 7 | |
| 15 | 2022 | 6 | |
| 16 | 2021 | 6 | |
| 17 | A Motivation-Based Action-Selection-Mechanism Involving Reinforcement Learning | 2008 | 5 |
| 18 | 2021 | 5 | |
| 19 | 2021 | 5 | |
| 20 | 2013 | 5 |
About Sanghoon Lee
Sanghoon Lee is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Biophysics, Molecular Biology and Signal Processing, having authored 46 papers that have together received 421 indexed citations. Recurring topics across this work include AI in cancer detection (10 papers), Medical Image Segmentation Techniques (4 papers), Topic Modeling (4 papers), Cell Image Analysis Techniques (4 papers), Speech Recognition and Synthesis (4 papers), Music and Audio Processing (3 papers), Semantic Web and Ontologies (3 papers) and Cancer Genomics and Diagnostics (3 papers). The work is most often cited by research in Health Informatics (12 citations), Biophysics (50 citations), Artificial Intelligence (210 citations), Signal Processing (43 citations) and Computer Vision and Pattern Recognition (79 citations). Sanghoon Lee has collaborated with scholars based in United States, South Korea and Philippines. Frequent co-authors include Lee Cooper, David A. Gutman, Jonathan Beezley, David Manthey, Seong–Whan Lee, Deepak R. Chittajallu, Mohammed Khalilia, Mohamed Amgad, Ji‐Hoon Kim and Mohamed Masoud. Their work appears in journals such as Cancer Research, Scientific Reports, iScience, Journal of Biomedical Informatics and Gynecologic Oncology.
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.