Yuanhe Tian
- Artificial Intelligence top 2%
- Topic Modeling 31
- Natural Language Processing Techniques 27
- Sentiment Analysis and Opinion Mining 7
- Advanced Text Analysis Techniques 5
- Speech and dialogue systems 3
- Health Informatics top 10%
- General Social Sciences top 5%
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- Multimodal Machine Learning Applications 6
- Information Systems top 10%
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- Radiomics and Machine Learning in Medical Imaging 4
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- Biomedical Text Mining and Ontologies 4
- Co-authors
- Yan SongGuimin ChenXiang WanFei XiaTong ZhangXiang AoYonggang WangNan Wang
- Journals
- BMC Bioinformatics (1 paper)Neurocomputing (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Yuanhe Tian
35 papers receiving 727 citations
Peers
Comparison fields: 5 of 42
- Artificial Intelligence 702
- Health Informatics 13
- General Social Sciences 16
- Computer Vision and Pattern Recognition 76
- Information Systems 51
Countries citing papers authored by Yuanhe Tian
This map shows the geographic impact of Yuanhe Tian'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 Yuanhe Tian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuanhe Tian more than expected).
Fields of papers citing papers by Yuanhe Tian
This network shows the impact of papers produced by Yuanhe Tian. 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 Yuanhe Tian. The network helps show where Yuanhe Tian may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yuanhe Tian, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 8 | |
| 2 | 2024 | 9 | |
| 3 | 2024 | 3 | |
| 4 | 2024 | 5 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 2 | |
| 7 | 2024 | 15 | |
| 8 | 2023 | 7 | |
| 9 | 2023 | 2 | |
| 10 | 2022 | 0 | |
| 11 | 2022 | 2 | |
| 12 | 2021 | 15 | |
| 13 | 2021 | 63 | |
| 14 | 2021 | 37 | |
| 15 | 2020 | 56 | |
| 16 | 2020 | 48 | |
| 17 | 2020 | 34 | |
| 18 | 2020 | 64 | |
| 19 | 2019 | 18 | |
| 20 | Lexical Knowledge Representation and Sense Prediction of Chinese Unknown Words | 2016 | 1 |
About Yuanhe Tian
Yuanhe Tian is a scholar working on Artificial Intelligence, General Social Sciences, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Information Systems, having authored 37 papers that have together received 742 indexed citations. Recurring topics across this work include Topic Modeling (31 papers), Natural Language Processing Techniques (27 papers), Sentiment Analysis and Opinion Mining (7 papers), Multimodal Machine Learning Applications (6 papers), Advanced Text Analysis Techniques (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Biomedical Text Mining and Ontologies (4 papers) and Speech and dialogue systems (3 papers). The work is most often cited by research in Artificial Intelligence (702 citations), Health Informatics (13 citations), General Social Sciences (16 citations), Computer Vision and Pattern Recognition (76 citations) and Information Systems (51 citations). Yuanhe Tian has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Yan Song, Guimin Chen, Xiang Wan, Fei Xia, Fei Xia, Tong Zhang, Xiang Ao, Yonggang Wang, Nan Wang and Yan Song. Their work appears in journals such as BMC Bioinformatics, Neurocomputing, arXiv (Cornell University), Proceedings of the AAAI Conference on Artificial Intelligence and Findings of the Association for Computational Linguistics: ACL 2022.
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.