Yining Hua
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
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- Digital Mental Health Interventions
Papers in
-
- Machine Learning in Healthcare 4
- Topic Modeling 3
-
- Mental Health via Writing 5
- Co-authors
- Shoukun Xu (1 shared paper)Yi Liu (1 shared paper)Jie Yang (8 shared papers)David W. Bates (3 shared papers)Peilin Zhou (8 shared papers)Li Zhou (1 shared paper)Joseph M. Plasek (1 shared paper)Li Zhou (5 shared papers)
- Journals
- Journal of Medical Internet Research (3 papers)Journal of the American Medical Informatics Association (2 papers)Journal of Biomedical Informatics (2 papers)Current Treatment Options in Psychiatry (1 paper)Neurocomputing (1 paper)
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Yining Hua
21 papers receiving 209 citations
Peers
Comparison fields: 5 of 74
- Health Informatics 14
- Applied Psychology 23
- General Social Sciences 7
- Computer Vision and Pattern Recognition 41
- Artificial Intelligence 61
Countries citing papers authored by Yining Hua
This map shows the geographic impact of Yining Hua'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 Yining Hua with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yining Hua more than expected).
Fields of papers citing papers by Yining Hua
This network shows the impact of papers produced by Yining Hua. 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 Yining Hua. The network helps show where Yining Hua may publish in the future.
Co-authors
The 25 scholars most cited alongside Yining Hua, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 42 | |
| 2 | 2022 | 32 | |
| 3 | 2025 | 21 | |
| 4 | 2024 | 17 | |
| 5 | 2022 | 14 | |
| 6 | 2023 | 12 | |
| 7 | 2023 | 12 | |
| 8 | 2023 | 11 | |
| 9 | 2023 | 10 | |
| 10 | 2023 | 10 | |
| 11 | 2024 | 6 | |
| 12 | 2025 | 5 | |
| 13 | 2024 | 5 | |
| 14 | 2023 | 5 | |
| 15 | 2024 | 4 | |
| 16 | 2025 | 3 | |
| 17 | 2024 | 2 | |
| 18 | 2025 | 1 | |
| 19 | 2024 | 1 | |
| 20 | 2025 | 1 |
About Yining Hua
Yining Hua is a scholar working on Artificial Intelligence, Social Psychology, Health Informatics, General Health Professions and Sociology and Political Science, having authored 26 papers that have together received 216 indexed citations. Recurring topics across this work include Mental Health via Writing (5 papers), Machine Learning in Healthcare (4 papers), Topic Modeling (3 papers), Artificial Intelligence in Healthcare and Education (3 papers), Digital Mental Health Interventions (2 papers), Misinformation and Its Impacts (2 papers), Recommender Systems and Techniques (2 papers) and Advanced Image and Video Retrieval Techniques (2 papers). The work is most often cited by research in Health Informatics (14 citations), Applied Psychology (23 citations), General Social Sciences (7 citations), Computer Vision and Pattern Recognition (41 citations) and Artificial Intelligence (61 citations). Yining Hua has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Shoukun Xu, Yi Liu, Jie Yang, David W. Bates, Peilin Zhou, Li Zhou, Joseph M. Plasek, Li Zhou, Minghui Li and Xian Wu. Their work appears in journals such as Journal of Medical Internet Research, Journal of the American Medical Informatics Association, Journal of Biomedical Informatics, Current Treatment Options in Psychiatry and Neurocomputing.
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.