Gao Yang
Impact in
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- Medical Image Segmentation Techniques
- Advanced Neural Network Applications
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- Radiomics and Machine Learning in Medical Imaging
- Advanced MRI Techniques and Applications
- Advanced Neuroimaging Techniques and Applications
- Retinal Imaging and Analysis
Papers in
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- Wireless Networks and Protocols 1
- IoT and Edge/Fog Computing 1
- Software-Defined Networks and 5G 1
- Co-authors
- Chris Taylor (1 shared paper)Daniel Rueckert (1 shared paper)David J. Hawkes (1 shared paper)Lie Xu (1 shared paper)Massoud Bazargan (1 shared paper)Wenjun Wu (3 shared papers)Pengbo Si (3 shared papers)Teng Sun (2 shared papers)
In The Last Decade
Gao Yang
10 papers receiving 1.3k citations
Gao Yang's Hit Papers
Peers
Comparison fields: 5 of 136
- Computer Vision and Pattern Recognition 521
- Radiology, Nuclear Medicine and Imaging 419
- Computational Mathematics 6
- Neurology 71
- Artificial Intelligence 285
Countries citing papers authored by Gao Yang
This map shows the geographic impact of Gao Yang'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 Gao Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gao Yang more than expected).
Fields of papers citing papers by Gao Yang
This network shows the impact of papers produced by Gao Yang. 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 Gao Yang. The network helps show where Gao Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside Gao Yang, 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 | Medical Image Computing and Computer-Assisted Intervention Hit paper breakdown → | 2009 | 1290 |
| 2 | 2013 | 35 | |
| 3 | 2024 | 8 | |
| 4 | 2022 | 7 | |
| 5 | トリオースキナーゼはフルクトースと食事耐性の脂質生成能を制御する【JST・京大機械翻訳】 | 2020 | 6 |
| 6 | 2023 | 4 | |
| 7 | 2024 | 2 | |
| 8 | 2025 | 1 | |
| 9 | 2024 | 1 | |
| 10 | 2017 | 1 |
About Gao Yang
Gao Yang is a scholar working on Computer Networks and Communications, Artificial Intelligence, Electrical and Electronic Engineering, Communication and Automotive Engineering, having authored 10 papers that have together received 1.4k indexed citations. Recurring topics across this work include Wireless Networks and Protocols (1 paper), IoT and Edge/Fog Computing (1 paper), Transportation and Mobility Innovations (1 paper), Software-Defined Networks and 5G (1 paper), Advanced MIMO Systems Optimization (1 paper), Blockchain Technology Applications and Security (1 paper), Public Relations and Crisis Communication (1 paper) and Advanced Image and Video Retrieval Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (521 citations), Radiology, Nuclear Medicine and Imaging (419 citations), Computational Mathematics (6 citations), Neurology (71 citations) and Artificial Intelligence (285 citations). Gao Yang has collaborated with scholars based in China, France and Canada. Frequent co-authors include Chris Taylor, Daniel Rueckert, David J. Hawkes, Lie Xu, Massoud Bazargan, Wenjun Wu, Pengbo Si, Teng Sun, Haipeng Huang and Yanhua Zhang. Their work appears in journals such as IEEE Transactions on Vehicular Technology, ACM Transactions on Knowledge Discovery from Data, IEEE Transactions on Wireless Communications, Cell Metabolism and HORMONES.
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.