Ho Bae
Impact in
- Hepatology top 10%
- Hepatitis C virus research
-
- Computational Drug Discovery Methods
Papers in
- Epidemiology 14
- Hepatitis B Virus Studies 13
- Liver Disease Diagnosis and Treatment 4
-
- Adversarial Robustness in Machine Learning 6
- Anomaly Detection Techniques and Applications 3
- Privacy-Preserving Technologies in Data 3
- Co-authors
- Sungroh Yoon (11 shared papers)Sunyoung Kwon (2 shared papers)Tse–Ling Fong (4 shared papers)Hyun-Soo Choi (4 shared papers)Brian T. Lee (2 shared papers)Seonwoo Min (2 shared papers)Calvin Q. Pan (5 shared papers)Linda S. Chan (1 shared paper)
- Journals
- IEEE Access (3 papers)Journal of Hepatology (3 papers)Digestive Diseases and Sciences (2 papers)Journal of Viral Hepatitis (2 papers)The American Journal of Gastroenterology (2 papers)
- Partner nations
- South KoreaUnited StatesChina
In The Last Decade
Ho Bae
32 papers receiving 486 citations
Peers
Comparison fields: 5 of 103
- Hepatology 81
- Computational Theory and Mathematics 114
- Epidemiology 140
- Health Informatics 4
- Signal Processing 25
Countries citing papers authored by Ho Bae
This map shows the geographic impact of Ho Bae'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 Ho Bae with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ho Bae more than expected).
Fields of papers citing papers by Ho Bae
This network shows the impact of papers produced by Ho Bae. 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 Ho Bae. The network helps show where Ho Bae may publish in the future.
Co-authors
The 25 scholars most cited alongside Ho Bae, 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 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 171 | |
| 2 | 2018 | 53 | |
| 3 | 2014 | 35 | |
| 4 | 2020 | 22 | |
| 5 | 2014 | 20 | |
| 6 | 2019 | 18 | |
| 7 | 2019 | 18 | |
| 8 | 2006 | 18 | |
| 9 | 2020 | 16 | |
| 10 | 2021 | 15 | |
| 11 | 2015 | 15 | |
| 12 | 2016 | 14 | |
| 13 | 2021 | 13 | |
| 14 | 2020 | 13 | |
| 15 | 2022 | 6 | |
| 16 | 2018 | 6 | |
| 17 | 2000 | 6 | |
| 18 | 2023 | 5 | |
| 19 | 2018 | 5 | |
| 20 | 2020 | 4 |
About Ho Bae
Ho Bae is a scholar working on Epidemiology, Artificial Intelligence, Hepatology, Computer Vision and Pattern Recognition and Infectious Diseases, having authored 37 papers that have together received 501 indexed citations. Recurring topics across this work include Hepatitis B Virus Studies (13 papers), Hepatitis C virus research (10 papers), Adversarial Robustness in Machine Learning (6 papers), Liver Disease Diagnosis and Treatment (4 papers), Anomaly Detection Techniques and Applications (3 papers), HIV/AIDS drug development and treatment (3 papers), Advanced Steganography and Watermarking Techniques (3 papers) and Privacy-Preserving Technologies in Data (3 papers). The work is most often cited by research in Hepatology (81 citations), Computational Theory and Mathematics (114 citations), Epidemiology (140 citations), Health Informatics (4 citations) and Signal Processing (25 citations). Ho Bae has collaborated with scholars based in South Korea, United States and China. Frequent co-authors include Sungroh Yoon, Sunyoung Kwon, Tse–Ling Fong, Hyun-Soo Choi, Brian T. Lee, Seonwoo Min, Calvin Q. Pan, Linda S. Chan, Sue Lee and Huy N. Trinh. Their work appears in journals such as IEEE Access, Journal of Hepatology, Digestive Diseases and Sciences, Journal of Viral Hepatitis and The American Journal of Gastroenterology.
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.