Hanxue Gu
- Health Informatics top 10%
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- Generative Adversarial Networks and Image Synthesis 2
- Medical Image Segmentation Techniques 2
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- Optical Imaging and Spectroscopy Techniques 2
- Infrared Thermography in Medicine 2
- Radiomics and Machine Learning in Medical Imaging 1
- Artificial Intelligence top 10%
- AI in cancer detection 4
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- Photoacoustic and Ultrasonic Imaging 2
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- Digital Radiography and Breast Imaging 2
- Co-authors
- Haoyu DongMaciej A. MazurowskiJichen YangNicholas KonzYixin ZhangBin DengStefan A. CarpKatharina Hoebel
- Cited by
- Health InformaticsComputer Vision and Pattern RecognitionRadiology, Nuclear Medicine and Imaging
- Journals
- Scientific Reports (1 paper)IEEE Transactions on Medical Imaging (3 papers)Medical Image Analysis (1 paper)
- Partner nations
- United States
In The Last Decade
Hanxue Gu
8 papers receiving 368 citations
Hit Papers
Peers
Comparison fields: 5 of 92
- Health Informatics 14
- Computer Vision and Pattern Recognition 140
- Radiology, Nuclear Medicine and Imaging 143
- Neurology 39
- Artificial Intelligence 100
Countries citing papers authored by Hanxue Gu
This map shows the geographic impact of Hanxue Gu'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 Hanxue Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hanxue Gu more than expected).
Fields of papers citing papers by Hanxue Gu
This network shows the impact of papers produced by Hanxue Gu. 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 Hanxue Gu. The network helps show where Hanxue Gu may publish in the future.
Co-authorship network
The 24 scholars most cited alongside Hanxue Gu, 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 | 2 | |
| 2 | 2025 | 5 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 0 | |
| 5 | 2025 | 1 | |
| 6 | 2025 | 0 | |
| 7 | 2024 | 4 | |
| 8 | 2024 | 0 | |
| 9 | 2023 | 7 | |
| 10 | Segment anything model for medical image analysis: An experimental studybreakdown → | 2023 | 342 |
| 11 | 2023 | 13 | |
| 12 | 2021 | 4 |
About Hanxue Gu
Hanxue Gu is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 12 papers that have together received 378 indexed citations. Recurring topics across this work include AI in cancer detection (4 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Medical Image Segmentation Techniques (2 papers), Optical Imaging and Spectroscopy Techniques (2 papers), Photoacoustic and Ultrasonic Imaging (2 papers), Digital Radiography and Breast Imaging (2 papers), Infrared Thermography in Medicine (2 papers) and Radiomics and Machine Learning in Medical Imaging (1 paper). The work is most often cited by research in Health Informatics (14 citations), Computer Vision and Pattern Recognition (140 citations) and Radiology, Nuclear Medicine and Imaging (143 citations). Hanxue Gu has collaborated with scholars based in United States. Frequent co-authors include Haoyu Dong, Maciej A. Mazurowski, Jichen Yang, Nicholas Konz, Yixin Zhang, Bin Deng, Stefan A. Carp, Katharina Hoebel, Jayashree Kalpathy–Cramer and Ken Chang. Their work appears in journals such as Scientific Reports, IEEE Transactions on Medical Imaging and Medical Image Analysis.
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.