Hanxue Gu

826 citations
12 papers · 378 indexed · 1 hit paper · h-index 5
Topics
AI in cancer detection (4 papers)Generative Adversarial Networks and Image Synthesis (2 papers)Medical Image Segmentation Techniques (2 papers)
Partner nations
United States

In The Last Decade

Hanxue Gu

8 papers receiving 368 citations

Hit Papers

Segment anything model for medical image analysis: An exp...20232026202420252023100200300

Peers

Hanxue Gu
Comparison fields: 5 of 92
  • Radiology, Nuclear Medicine and Imaging 143
  • Computer Vision and Pattern Recognition 140
  • Artificial Intelligence 100
  • Biomedical Engineering 64
  • Neurology 39
Replace Haoyu Dong with:
Haoyu Dong United States
Nicholas Konz United States
Jichen Yang United States
Kejuan Yue China
Cheng Bian China
Tianbao Zhou China
Luana Batista da Cruz Brazil
Chaoyu Chen China
Jeremiah Neubert United States
Hanxue Gu relative to Haoyu Dong United States Haoyu Dong's profile →
Citations per field
00.5×1.5×
Haoyu Dong · 1×
Citations per year

Countries citing papers authored by Hanxue Gu

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Hanxue Gu

This figure shows the co-authorship network connecting the top 25 collaborators of Hanxue Gu. A scholar is included among the top collaborators of Hanxue Gu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hanxue Gu. Hanxue Gu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
#WorkIndexed citations
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2 5
3 0
4 0
5 1
6 0
7 4
8 0
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Segment anything model for medical image analysis: An experimental studybreakdown →
342
11 13
12 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) and Medical Image Segmentation Techniques (2 papers). 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.

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