Dan Pan
Impact in
- Neurology top 5%
- Brain Tumor Detection and Classification
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- Artificial Intelligence in Healthcare
Papers in
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- AI in cancer detection 3
- Machine Learning in Healthcare 3
- Co-authors
- An Zeng (18 shared papers)Xiaowei Song (6 shared papers)Tory O. Frizzell (2 shared papers)Longfei Jia (4 shared papers)Yin Huang (1 shared paper)Ruixuan Wang (1 shared paper)Shen Zhao (1 shared paper)Bin Chen (1 shared paper)
In The Last Decade
Dan Pan
24 papers receiving 449 citations
Peers
Comparison fields: 5 of 85
- Neurology 186
- Health Information Management 69
- Health Informatics 20
- Psychiatry and Mental health 130
- Artificial Intelligence 187
Countries citing papers authored by Dan Pan
This map shows the geographic impact of Dan Pan'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 Dan Pan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Pan more than expected).
Fields of papers citing papers by Dan Pan
This network shows the impact of papers produced by Dan Pan. 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 Dan Pan. The network helps show where Dan Pan may publish in the future.
Co-authors
The 25 scholars most cited alongside Dan Pan, 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 204 | |
| 2 | 2022 | 79 | |
| 3 | 2022 | 67 | |
| 4 | 2006 | 31 | |
| 5 | 2022 | 19 | |
| 6 | 2022 | 19 | |
| 7 | 2024 | 8 | |
| 8 | 2021 | 8 | |
| 9 | 2025 | 4 | |
| 10 | 2024 | 4 | |
| 11 | 2018 | 4 | |
| 12 | 2010 | 4 | |
| 13 | 2021 | 4 | |
| 14 | 2023 | 3 | |
| 15 | 2020 | 3 | |
| 16 | 2005 | 3 | |
| 17 | 2025 | 2 | |
| 18 | 2019 | 2 | |
| 19 | 2022 | 1 | |
| 20 | 2006 | 1 |
About Dan Pan
Dan Pan is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Neurology, Psychiatry and Mental health and Computer Vision and Pattern Recognition, having authored 28 papers that have together received 474 indexed citations. Recurring topics across this work include Dementia and Cognitive Impairment Research (7 papers), Brain Tumor Detection and Classification (6 papers), AI in cancer detection (3 papers), Neurological Disease Mechanisms and Treatments (3 papers), Functional Brain Connectivity Studies (3 papers), Machine Learning in Healthcare (3 papers), Advanced Neural Network Applications (2 papers) and Remote Sensing and LiDAR Applications (2 papers). The work is most often cited by research in Neurology (186 citations), Health Information Management (69 citations), Health Informatics (20 citations), Psychiatry and Mental health (130 citations) and Artificial Intelligence (187 citations). Dan Pan has collaborated with scholars based in China, Canada and Sweden. Frequent co-authors include An Zeng, Xiaowei Song, Tory O. Frizzell, Longfei Jia, Yin Huang, Ruixuan Wang, Shen Zhao, Bin Chen, Ryan C.N. D’Arcy and Sujoy Ghosh Hajra. Their work appears in journals such as Alzheimer s & Dementia, Health Information Science and Systems, IEEE Journal of Biomedical and Health Informatics, Frontiers in Neuroscience and Computer Methods and Programs in Biomedicine.
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.