Peng Cao
Impact in
- Computational Mathematics top 10%
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- Artificial Intelligence in Healthcare
Papers in
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- Imbalanced Data Classification Techniques 10
- Domain Adaptation and Few-Shot Learning 4
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- Functional Brain Connectivity Studies 8
- Co-authors
- Osmar R. Zai͏̈ane (22 shared papers)Jinzhu Yang (15 shared papers)Dazhe Zhao (17 shared papers)Xiaoli Liu (7 shared papers)Min Huang (7 shared papers)Dina Katabi (1 shared paper)Rogério Feris (1 shared paper)Lijie Fan (1 shared paper)
In The Last Decade
Peng Cao
35 papers receiving 788 citations
Peers
Comparison fields: 5 of 102
- Computational Mathematics 12
- Health Information Management 62
- Neurology 86
- Artificial Intelligence 341
- Radiology, Nuclear Medicine and Imaging 216
Countries citing papers authored by Peng Cao
This map shows the geographic impact of Peng Cao'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 Peng Cao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peng Cao more than expected).
Fields of papers citing papers by Peng Cao
This network shows the impact of papers produced by Peng Cao. 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 Peng Cao. The network helps show where Peng Cao may publish in the future.
Co-authors
The 25 scholars most cited alongside Peng Cao, 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 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 161 | |
| 2 | 2022 | 113 | |
| 3 | 2016 | 58 | |
| 4 | 2017 | 44 | |
| 5 | 2021 | 39 | |
| 6 | 2013 | 39 | |
| 7 | 2018 | 33 | |
| 8 | 2017 | 30 | |
| 9 | 2016 | 30 | |
| 10 | 2022 | 24 | |
| 11 | 2018 | 21 | |
| 12 | 2022 | 20 | |
| 13 | 2018 | 19 | |
| 14 | 2019 | 17 | |
| 15 | 2018 | 16 | |
| 16 | 2022 | 15 | |
| 17 | 2023 | 14 | |
| 18 | 2022 | 14 | |
| 19 | 2016 | 12 | |
| 20 | 2021 | 12 |
About Peng Cao
Peng Cao is a scholar working on Artificial Intelligence, Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging, Health Information Management and Psychiatry and Mental health, having authored 37 papers that have together received 800 indexed citations. Recurring topics across this work include Imbalanced Data Classification Techniques (10 papers), Functional Brain Connectivity Studies (8 papers), Artificial Intelligence in Healthcare (6 papers), Retinal Imaging and Analysis (5 papers), Dementia and Cognitive Impairment Research (5 papers), Domain Adaptation and Few-Shot Learning (4 papers), Electricity Theft Detection Techniques (4 papers) and Brain Tumor Detection and Classification (3 papers). The work is most often cited by research in Computational Mathematics (12 citations), Health Information Management (62 citations), Neurology (86 citations), Artificial Intelligence (341 citations) and Radiology, Nuclear Medicine and Imaging (216 citations). Peng Cao has collaborated with scholars based in China, Canada and Singapore. Frequent co-authors include Osmar R. Zai͏̈ane, Jinzhu Yang, Dazhe Zhao, Xiaoli Liu, Min Huang, Dina Katabi, Rogério Feris, Lijie Fan, Yuzhe Yang and Tianhong Li. Their work appears in journals such as Computerized Medical Imaging and Graphics, Computers in Biology and Medicine, Computer Methods and Programs in Biomedicine, Neuroinformatics and ACM Transactions on Knowledge Discovery from Data.
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.