Mei Chen
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- Digital Imaging for Blood Diseases 7
- Artificial Intelligence top 2%
- AI in cancer detection 10
- Biophysics top 2%
- Cell Image Analysis Techniques 8
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- Air Quality and Health Impacts 10
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- Atmospheric chemistry and aerosols 9
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- Complex Network Analysis Techniques 8
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- earthquake and tectonic studies 6
- Geological and Geochemical Analysis 5
- Journals
- SHILAP Revista de lepidopterología (1 paper)Environmental Science & Technology (1 paper)Journal of Agricultural and Food Chemistry (1 paper)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Mei Chen
78 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 152
- Computer Vision and Pattern Recognition 508
- Artificial Intelligence 739
- Biophysics 116
- Health, Toxicology and Mutagenesis 184
- Radiology, Nuclear Medicine and Imaging 302
Countries citing papers authored by Mei Chen
This map shows the geographic impact of Mei Chen'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 Mei Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mei Chen more than expected).
Fields of papers citing papers by Mei Chen
This network shows the impact of papers produced by Mei Chen. 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 Mei Chen. The network helps show where Mei Chen may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mei Chen, 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 | 2025 | 0 | |
| 2 | 2025 | 4 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 3 | |
| 6 | 2024 | 7 | |
| 7 | 2024 | 0 | |
| 8 | 2020 | 2 | |
| 9 | 2019 | 3 | |
| 10 | 2019 | 0 | |
| 11 | 2018 | 76 | |
| 12 | 2017 | 53 | |
| 13 | 2017 | 39 | |
| 14 | 2017 | 2 | |
| 15 | 2016 | 27 | |
| 16 | 2016 | 52 | |
| 17 | 2014 | 19 | |
| 18 | 2010 | 43 | |
| 19 | Formation of Multi-Objective Dynamic Cells Using Random Weight Multi-Objective Genetic Algorithm | 2008 | 1 |
| 20 | A Texture Recognition Technology Based on Neural Network | 2003 | 1 |
About Mei Chen
Mei Chen is a scholar working on Biophysics, Computer Vision and Pattern Recognition and Health, Toxicology and Mutagenesis, having authored 87 papers that have together received 1.8k indexed citations. Recurring topics across this work include Air Quality and Health Impacts (10 papers), AI in cancer detection (10 papers), Atmospheric chemistry and aerosols (9 papers), Cell Image Analysis Techniques (8 papers), Complex Network Analysis Techniques (8 papers), Digital Imaging for Blood Diseases (7 papers), earthquake and tectonic studies (6 papers) and Geological and Geochemical Analysis (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (508 citations), Artificial Intelligence (739 citations) and Biophysics (116 citations). Mei Chen has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Weidong Cai, Dagan Feng, Yun Zhou, Qing Li, Xiaogang Wang, Yang Song, Heng Huang, Songjun Guo, Afaf Tareef and Jihua Tan. Their work appears in journals such as SHILAP Revista de lepidopterología, Environmental Science & Technology and Journal of Agricultural and Food Chemistry.
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.