Hang Dong
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
Papers in
-
- Biomedical Text Mining and Ontologies 8
- Histone Deacetylase Inhibitors Research 4
-
- Topic Modeling 17
- Natural Language Processing Techniques 10
- Semantic Web and Ontologies 10
- Machine Learning in Healthcare 7
- Advanced Text Analysis Techniques 4
- Co-authors
- Huaiqun Guan (1 shared paper)Honghan Wu (10 shared papers)Chunlong Zhao (6 shared papers)Yingjie Zhang (7 shared papers)William Whiteley (5 shared papers)Víctor Suárez-Paniagua (6 shared papers)Beatrice Alex (7 shared papers)Jiaoyan Chen (11 shared papers)
- Journals
- BMC Medical Informatics and Decision Making (2 papers)Molecules (2 papers)Medical Physics (2 papers)Remote Sensing (2 papers)Energies (2 papers)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Hang Dong
88 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 147
- Health Informatics 65
- Health Information Management 73
- Radiation 77
- Pharmacology 72
- Artificial Intelligence 286
Countries citing papers authored by Hang Dong
This map shows the geographic impact of Hang Dong'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 Hang Dong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hang Dong more than expected).
Fields of papers citing papers by Hang Dong
This network shows the impact of papers produced by Hang Dong. 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 Hang Dong. The network helps show where Hang Dong may publish in the future.
Co-authors
The 25 scholars most cited alongside Hang Dong, 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 98 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 121 | |
| 2 | 2020 | 111 | |
| 3 | 2009 | 91 | |
| 4 | 2011 | 82 | |
| 5 | 2021 | 54 | |
| 6 | 2022 | 53 | |
| 7 | 2010 | 49 | |
| 8 | 2019 | 47 | |
| 9 | 2019 | 43 | |
| 10 | 2019 | 38 | |
| 11 | 2021 | 36 | |
| 12 | 2023 | 30 | |
| 13 | 2022 | 30 | |
| 14 | 2023 | 29 | |
| 15 | 2021 | 26 | |
| 16 | 2018 | 25 | |
| 17 | 2022 | 23 | |
| 18 | 2006 | 22 | |
| 19 | 2023 | 20 | |
| 20 | 2023 | 16 |
About Hang Dong
Hang Dong is a scholar working on Molecular Biology, Artificial Intelligence, Electrical and Electronic Engineering, Biomedical Engineering and Cancer Research, having authored 98 papers that have together received 1.3k indexed citations. Recurring topics across this work include Topic Modeling (17 papers), Natural Language Processing Techniques (10 papers), Semantic Web and Ontologies (10 papers), Biomedical Text Mining and Ontologies (8 papers), Machine Learning in Healthcare (7 papers), Histone Deacetylase Inhibitors Research (4 papers), Advanced Text Analysis Techniques (4 papers) and Geophysical Methods and Applications (4 papers). The work is most often cited by research in Health Informatics (65 citations), Health Information Management (73 citations), Radiation (77 citations), Pharmacology (72 citations) and Artificial Intelligence (286 citations). Hang Dong has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Huaiqun Guan, Honghan Wu, Chunlong Zhao, Yingjie Zhang, William Whiteley, Víctor Suárez-Paniagua, Beatrice Alex, Jiaoyan Chen, Zhi‐Hong Jiang and Vincent Kam Wai Wong. Their work appears in journals such as BMC Medical Informatics and Decision Making, Molecules, Medical Physics, Remote Sensing and Energies.
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.