Chao Che
Impact in
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- Artificial Intelligence in Healthcare
- Health Informatics top 10%
Papers in ⓘ
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- Topic Modeling 9
- Natural Language Processing Techniques 6
- AI in cancer detection 4
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- Biomedical Text Mining and Ontologies 8
- Bioinformatics and Genomic Networks 8
- Machine Learning in Bioinformatics 4
- Co-authors
- Bo Jin (12 shared papers)Peiliang Zhang (14 shared papers)Xiaopeng Wei (11 shared papers)Yongjun Zhu (12 shared papers)Qiang Zhang (17 shared papers)Yue Qu (2 shared papers)Zhen Liu (1 shared paper)Xiaomeng Yin (1 shared paper)
- Journals
- Knowledge-Based Systems (4 papers)Mathematical Biosciences & Engineering (3 papers)Future Internet (2 papers)International Journal of Machine Learning and Cybernetics (2 papers)BMC Bioinformatics (2 papers)
- Partner nations
- ChinaSouth KoreaEthiopia
In The Last Decade
Chao Che
50 papers receiving 763 citations
Peers
Comparison fields: 5 of 108
- Health Information Management 96
- Health Informatics 17
- Computational Theory and Mathematics 169
- Artificial Intelligence 296
- General Dentistry 15
Countries citing papers authored by Chao Che
This map shows the geographic impact of Chao Che'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 Chao Che with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chao Che more than expected).
Fields of papers citing papers by Chao Che
This network shows the impact of papers produced by Chao Che. 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 Chao Che. The network helps show where Chao Che may publish in the future.
Co-authors
The 25 scholars most cited alongside Chao Che, 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 59 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 113 | |
| 2 | 2021 | 106 | |
| 3 | 2022 | 66 | |
| 4 | 2020 | 41 | |
| 5 | 2021 | 30 | |
| 6 | 2009 | 30 | |
| 7 | 2023 | 29 | |
| 8 | 2021 | 28 | |
| 9 | 2008 | 26 | |
| 10 | 2021 | 25 | |
| 11 | 2022 | 25 | |
| 12 | 2021 | 24 | |
| 13 | 2024 | 21 | |
| 14 | 2014 | 21 | |
| 15 | 2023 | 21 | |
| 16 | 2020 | 21 | |
| 17 | 2019 | 15 | |
| 18 | 2022 | 14 | |
| 19 | 2020 | 12 | |
| 20 | 2014 | 11 |
About Chao Che
Chao Che is a scholar working on Artificial Intelligence, Molecular Biology, Computational Theory and Mathematics, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, having authored 59 papers that have together received 793 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (15 papers), Topic Modeling (9 papers), Biomedical Text Mining and Ontologies (8 papers), Bioinformatics and Genomic Networks (8 papers), Natural Language Processing Techniques (6 papers), Machine Learning in Bioinformatics (4 papers), Machine Learning in Materials Science (4 papers) and AI in cancer detection (4 papers). The work is most often cited by research in Health Information Management (96 citations), Health Informatics (17 citations), Computational Theory and Mathematics (169 citations), Artificial Intelligence (296 citations) and General Dentistry (15 citations). Chao Che has collaborated with scholars based in China, South Korea and Ethiopia. Frequent co-authors include Bo Jin, Peiliang Zhang, Xiaopeng Wei, Yongjun Zhu, Qiang Zhang, Yue Qu, Zhen Liu, Xiaomeng Yin, Ziqi Wei and Bo Jin. Their work appears in journals such as Knowledge-Based Systems, Mathematical Biosciences & Engineering, Future Internet, International Journal of Machine Learning and Cybernetics and BMC Bioinformatics.
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.