Jin Ge
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
- Hepatology top 5%
- Liver Disease and Transplantation
Papers in
- Hepatology 17
- Liver Disease and Transplantation 16
- Surgery 16
- Organ Transplantation Techniques and Outcomes 14
- Co-authors
- Jennifer C. Lai (33 shared papers)Mark J. Pletcher (12 shared papers)Jeremy Harper (1 shared paper)Christopher G. Chute (1 shared paper)Melissa Haendel (1 shared paper)Michael Li (1 shared paper)John C. Bucuvalas (3 shared papers)Richard Gilroy (2 shared papers)
- Journals
- Hepatology (10 papers)Hepatology Communications (5 papers)American Journal of Transplantation (4 papers)The American Journal of Gastroenterology (3 papers)Liver Transplantation (3 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Jin Ge
64 papers receiving 801 citations
Peers
Comparison fields: 5 of 122
- Health Informatics 80
- Hepatology 181
- Transplantation 20
- Geriatrics and Gerontology 22
- Health Information Management 25
Countries citing papers authored by Jin Ge
This map shows the geographic impact of Jin Ge'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 Jin Ge with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jin Ge more than expected).
Fields of papers citing papers by Jin Ge
This network shows the impact of papers produced by Jin Ge. 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 Jin Ge. The network helps show where Jin Ge may publish in the future.
Co-authors
The 25 scholars most cited alongside Jin Ge, 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 75 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 82 | |
| 2 | 2024 | 76 | |
| 3 | 2020 | 67 | |
| 4 | 2023 | 54 | |
| 5 | 2023 | 46 | |
| 6 | 2008 | 40 | |
| 7 | 2012 | 39 | |
| 8 | 2022 | 33 | |
| 9 | 2023 | 32 | |
| 10 | 2021 | 31 | |
| 11 | 2019 | 27 | |
| 12 | 2024 | 22 | |
| 13 | 2018 | 20 | |
| 14 | 2025 | 18 | |
| 15 | 2019 | 17 | |
| 16 | 2018 | 16 | |
| 17 | 2021 | 15 | |
| 18 | 2022 | 11 | |
| 19 | 2022 | 11 | |
| 20 | 2022 | 10 |
About Jin Ge
Jin Ge is a scholar working on Hepatology, Surgery, Epidemiology, Artificial Intelligence and Infectious Diseases, having authored 75 papers that have together received 812 indexed citations. Recurring topics across this work include Liver Disease and Transplantation (16 papers), Organ Transplantation Techniques and Outcomes (14 papers), Liver Disease Diagnosis and Treatment (9 papers), Machine Learning in Healthcare (5 papers), COVID-19 Clinical Research Studies (4 papers), Artificial Intelligence in Healthcare and Education (4 papers), Renal Transplantation Outcomes and Treatments (3 papers) and Terahertz technology and applications (3 papers). The work is most often cited by research in Health Informatics (80 citations), Hepatology (181 citations), Transplantation (20 citations), Geriatrics and Gerontology (22 citations) and Health Information Management (25 citations). Jin Ge has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Jennifer C. Lai, Mark J. Pletcher, Jeremy Harper, Christopher G. Chute, Melissa Haendel, Michael Li, John C. Bucuvalas, Richard Gilroy, Joseph F. Owens and W. Ray Kim. Their work appears in journals such as Hepatology, Hepatology Communications, American Journal of Transplantation, The American Journal of Gastroenterology and Liver Transplantation.
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.