Yi Gao
- Health Informatics top 2%
-
- Radiomics and Machine Learning in Medical Imaging 17
- Medical Imaging Techniques and Applications 8
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- Medical Image Segmentation Techniques 23
- Image Retrieval and Classification Techniques 6
- Advanced Neural Network Applications 6
- Biophysics top 2%
- Cell Image Analysis Techniques 9
- Artificial Intelligence top 1%
- AI in cancer detection 20
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- Pancreatic and Hepatic Oncology Research 5
- Co-authors
- Tahsin KurçJoel SaltzGeorge M. ChurchLe HouDimitris SamarasJames DavisAllen TannenbaumSylvain Bouix
- Cited by
- Health InformaticsRadiology, Nuclear Medicine and ImagingComputer Vision and Pattern Recognition
- Journals
- Medical Image Analysis (4 papers)IEEE Transactions on Image Processing (3 papers)IEEE Access (3 papers)
- Partner nations
- ChinaUnited StatesIsrael
In The Last Decade
Yi Gao
102 papers receiving 2.1k citations
Hit Papers
Peers
Comparison fields: 5 of 158
- Health Informatics 68
- Radiology, Nuclear Medicine and Imaging 764
- Computer Vision and Pattern Recognition 626
- Biophysics 167
- Artificial Intelligence 845
Countries citing papers authored by Yi Gao
This map shows the geographic impact of Yi Gao'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 Yi Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yi Gao more than expected).
Fields of papers citing papers by Yi Gao
This network shows the impact of papers produced by Yi Gao. 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 Yi Gao. The network helps show where Yi Gao may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yi Gao, 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 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 2 | |
| 7 | 2023 | 3 | |
| 8 | 2023 | 1 | |
| 9 | 2023 | 2 | |
| 10 | 2023 | 1 | |
| 11 | 2022 | 20 | |
| 12 | 2022 | 14 | |
| 13 | 2021 | 90 | |
| 14 | 2021 | 5 | |
| 15 | 2018 | 151 | |
| 16 | 2017 | 33 | |
| 17 | 2016 | 5 | |
| 18 | 2015 | 20 | |
| 19 | On the Simulation of Networked Sensor Systems. | 2015 | 1 |
| 20 | Optical flow based techniques for ExoMars rover autonomous navigation | 2008 | 2 |
About Yi Gao
Yi Gao is a scholar working on Computer Vision and Pattern Recognition, Biophysics and Radiology, Nuclear Medicine and Imaging, having authored 109 papers that have together received 2.1k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (23 papers), AI in cancer detection (20 papers), Radiomics and Machine Learning in Medical Imaging (17 papers), Cell Image Analysis Techniques (9 papers), Medical Imaging Techniques and Applications (8 papers), Image Retrieval and Classification Techniques (6 papers), Advanced Neural Network Applications (6 papers) and Pancreatic and Hepatic Oncology Research (5 papers). The work is most often cited by research in Health Informatics (68 citations), Radiology, Nuclear Medicine and Imaging (764 citations) and Computer Vision and Pattern Recognition (626 citations). Yi Gao has collaborated with scholars based in China, United States and Israel. Frequent co-authors include Tahsin Kurç, Joel Saltz, George M. Church, Le Hou, Dimitris Samaras, James Davis, Allen Tannenbaum, Sylvain Bouix, Chuan Huang and Karl Spuhler. Their work appears in journals such as Medical Image Analysis, IEEE Transactions on Image Processing, IEEE Access, SIAM Journal on Imaging Sciences and 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.