Xiaoyu He
Impact in
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- Cutaneous Melanoma Detection and Management
- Human-Computer Interaction top 10%
- Hand Gesture Recognition Systems
Papers in
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- AI in cancer detection 6
- Natural Language Processing Techniques 3
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- Multimodal Machine Learning Applications 5
- Advanced Neural Network Applications 3
- Co-authors
- Shuang Zhao (9 shared papers)Xiang Chen (5 shared papers)Bin Xie (4 shared papers)Weihong Huang (4 shared papers)Yong Wang (1 shared paper)Xian Wu (3 shared papers)Yi Li (1 shared paper)Kai Huang (3 shared papers)
- Journals
- Complex & Intelligent Systems (3 papers)Neurocomputing (2 papers)Clinical & Translational Oncology (1 paper)Acta Pharmaceutica Sinica B (1 paper)Scientific Reports (1 paper)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Xiaoyu He
40 papers receiving 482 citations
Xiaoyu He's Hit Papers
Peers
Comparison fields: 5 of 108
- Oncology 168
- Human-Computer Interaction 33
- Artificial Intelligence 144
- Computer Vision and Pattern Recognition 89
- Dermatology 30
Countries citing papers authored by Xiaoyu He
This map shows the geographic impact of Xiaoyu He'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 Xiaoyu He with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoyu He more than expected).
Fields of papers citing papers by Xiaoyu He
This network shows the impact of papers produced by Xiaoyu He. 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 Xiaoyu He. The network helps show where Xiaoyu He may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaoyu He, 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 53 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 104 | |
| 2 | 2022 | 45 | |
| 3 | 2020 | 37 | |
| 4 | Two-dimensional Czochralski growth of single-crystal MoS2 Hit paper breakdown → | 2025 | 32 |
| 5 | 2018 | 31 | |
| 6 | 2022 | 30 | |
| 7 | 2019 | 23 | |
| 8 | 2022 | 23 | |
| 9 | 2023 | 22 | |
| 10 | 2021 | 16 | |
| 11 | 2016 | 15 | |
| 12 | 2022 | 12 | |
| 13 | 2020 | 11 | |
| 14 | 2007 | 11 | |
| 15 | 2012 | 11 | |
| 16 | 2019 | 9 | |
| 17 | 2022 | 9 | |
| 18 | 2008 | 7 | |
| 19 | 2019 | 6 | |
| 20 | 2024 | 5 |
About Xiaoyu He
Xiaoyu He is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Oncology, Materials Chemistry and Mechanical Engineering, having authored 53 papers that have together received 507 indexed citations. Recurring topics across this work include Cutaneous Melanoma Detection and Management (7 papers), AI in cancer detection (6 papers), Multimodal Machine Learning Applications (5 papers), Nonmelanoma Skin Cancer Studies (5 papers), Language, Metaphor, and Cognition (4 papers), Advanced Neural Network Applications (3 papers), Natural Language Processing Techniques (3 papers) and 2D Materials and Applications (3 papers). The work is most often cited by research in Oncology (168 citations), Human-Computer Interaction (33 citations), Artificial Intelligence (144 citations), Computer Vision and Pattern Recognition (89 citations) and Dermatology (30 citations). Xiaoyu He has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Shuang Zhao, Xiang Chen, Bin Xie, Weihong Huang, Yong Wang, Xian Wu, Yi Li, Kai Huang, Zhe Wu and Yong Wang. Their work appears in journals such as Complex & Intelligent Systems, Neurocomputing, Clinical & Translational Oncology, Acta Pharmaceutica Sinica B and Scientific Reports.
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.