Xiaohong Gao

4.2k total citations
115 papers, 2.2k citations indexed

About

Xiaohong Gao is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Xiaohong Gao has authored 115 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Computer Vision and Pattern Recognition, 27 papers in Radiology, Nuclear Medicine and Imaging and 17 papers in Artificial Intelligence. Recurrent topics in Xiaohong Gao's work include AI in cancer detection (13 papers), Radiomics and Machine Learning in Medical Imaging (12 papers) and Color Science and Applications (11 papers). Xiaohong Gao is often cited by papers focused on AI in cancer detection (13 papers), Radiomics and Machine Learning in Medical Imaging (12 papers) and Color Science and Applications (11 papers). Xiaohong Gao collaborates with scholars based in China, United Kingdom and United States. Xiaohong Gao's co-authors include Rui Hui, Richard J. Shavelson, Gail P. Baxter, Zengmin Tian, D. G. Shaposhnikov, L. N. Podladchikova, Natalia A. Shevtsova, Robert L. Brennan, Qian Yu and Martin Loomes and has published in prestigious journals such as PLoS ONE, Scientific Reports and American Journal of Epidemiology.

In The Last Decade

Xiaohong Gao

110 papers receiving 2.0k citations

Peers

Xiaohong Gao
Comparison fields: 5 of 174
  • Computer Vision and Pattern Recognition 646
  • Radiology, Nuclear Medicine and Imaging 526
  • Artificial Intelligence 362
  • Epidemiology 232
  • Education 215
Replace Xiaofeng Liu with:
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Kostas Marias Greece
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Xujuan Zhou Australia
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Xiaofeng Liu United States View profile →
Citations per field, relative to Xiaohong Gao
Xiaohong Gao · 1×
Citations per year, relative to Xiaohong Gao
Xiaohong Gao · 1×

Countries citing papers authored by Xiaohong Gao

Since Specialization
Citations

This map shows the geographic impact of Xiaohong 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 Xiaohong Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaohong Gao more than expected).

Fields of papers citing papers by Xiaohong Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiaohong 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 Xiaohong Gao. The network helps show where Xiaohong Gao may publish in the future.

Co-authorship network of co-authors of Xiaohong Gao

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaohong Gao. A scholar is included among the top collaborators of Xiaohong Gao 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 Xiaohong Gao. Xiaohong Gao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 1
2 0
3 1
4 1
5 2
6 1
7 0
8 13
9 1
10 26
11 2
12 9
13
Transfer learning for endoscopy disease detection and segmentation with MASk-RCNN benchmark architecture
4
14
Application of deep learning neural network for classification of TB lung CT images based on patches
1
15
MIRAGE: An E-repository of Medical Images for Learning Biomedical Informatics
1
16
Retrieval of 3D medical images via their texture features
8
17 1
18 1
19 3
20
Extraction of Sagittal Symmetry Planes from Pet Images.
5

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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