Eric A. Geng
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
-
- Medical Coding and Health Information
- Artificial Intelligence in Healthcare
Papers in
-
- Medical Coding and Health Information 3
- Artificial Intelligence in Healthcare 2
- Surgery 11
- Cervical and Thoracic Myelopathy 7
- Co-authors
- Samuel Kang-Wook Cho (21 shared papers)Jun Kim (18 shared papers)Brian Cho (8 shared papers)Varun Arvind (10 shared papers)Seema Bhatnagar (2 shared papers)Kimberly R. Urban (2 shared papers)J Schwartz (4 shared papers)Justin E. Tang (9 shared papers)
- Journals
- Global Spine Journal (5 papers)World Neurosurgery (2 papers)Clinical Spine Surgery A Spine Publication (2 papers)The Spine Journal (2 papers)Neurospine (2 papers)
- Partner nations
- United States
In The Last Decade
Eric A. Geng
21 papers receiving 301 citations
Peers
Comparison fields: 5 of 52
- Health Informatics 88
- Health Information Management 57
- Behavioral Neuroscience 14
- Surgery 69
- Artificial Intelligence 51
Countries citing papers authored by Eric A. Geng
This map shows the geographic impact of Eric A. Geng'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 Eric A. Geng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric A. Geng more than expected).
Fields of papers citing papers by Eric A. Geng
This network shows the impact of papers produced by Eric A. Geng. 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 Eric A. Geng. The network helps show where Eric A. Geng may publish in the future.
Co-authors
The 25 scholars most cited alongside Eric A. Geng, 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 49 | |
| 2 | 2022 | 41 | |
| 3 | 2019 | 34 | |
| 4 | 2023 | 23 | |
| 5 | 2019 | 22 | |
| 6 | 2019 | 20 | |
| 7 | 2022 | 17 | |
| 8 | 2023 | 16 | |
| 9 | 2022 | 15 | |
| 10 | 2022 | 14 | |
| 11 | 2022 | 12 | |
| 12 | 2022 | 11 | |
| 13 | 2023 | 7 | |
| 14 | 2021 | 6 | |
| 15 | 2021 | 5 | |
| 16 | 2021 | 3 | |
| 17 | 2023 | 3 | |
| 18 | 2024 | 3 | |
| 19 | 2024 | 2 | |
| 20 | 2023 | 1 |
About Eric A. Geng
Eric A. Geng is a scholar working on Health Information Management, Surgery, Health Informatics, Artificial Intelligence and Behavioral Neuroscience, having authored 23 papers that have together received 305 indexed citations. Recurring topics across this work include Cervical and Thoracic Myelopathy (7 papers), Machine Learning in Healthcare (7 papers), Artificial Intelligence in Healthcare and Education (3 papers), Medical Coding and Health Information (3 papers), Biomedical Text Mining and Ontologies (2 papers), Artificial Intelligence in Healthcare (2 papers), Stress Responses and Cortisol (2 papers) and COVID-19 Clinical Research Studies (1 paper). The work is most often cited by research in Health Informatics (88 citations), Health Information Management (57 citations), Behavioral Neuroscience (14 citations), Surgery (69 citations) and Artificial Intelligence (51 citations). Eric A. Geng has collaborated with scholars based in United States. Frequent co-authors include Samuel Kang-Wook Cho, Jun Kim, Brian Cho, Varun Arvind, Seema Bhatnagar, Kimberly R. Urban, J Schwartz, Justin E. Tang, Bashar Zaidat and Michael C. Gao. Their work appears in journals such as Global Spine Journal, World Neurosurgery, Clinical Spine Surgery A Spine Publication, The Spine Journal and Neurospine.
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.