Shaoya Guan

20 total papers · 659 total citations
15 papers, 517 citations indexed

About

Shaoya Guan is a scholar working on Biomedical Engineering, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Shaoya Guan has authored 15 papers receiving a total of 517 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Biomedical Engineering, 7 papers in Computer Vision and Pattern Recognition and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Shaoya Guan's work include Medical Image Segmentation Techniques (6 papers), Soft Robotics and Applications (5 papers) and Medical Imaging Techniques and Applications (4 papers). Shaoya Guan is often cited by papers focused on Medical Image Segmentation Techniques (6 papers), Soft Robotics and Applications (5 papers) and Medical Imaging Techniques and Applications (4 papers). Shaoya Guan collaborates with scholars based in China. Shaoya Guan's co-authors include Tianmiao Wang, Li Wen, Yufei Hao, Xingbang Yang, Zheyuan Gong, Zhexin Xie, Ziyu Ren, Meng Cai, Qi Wang and Hui Wang and has published in prestigious journals such as IEEE Access, Neurocomputing and IEEE Journal of Biomedical and Health Informatics.

In The Last Decade

Shaoya Guan

13 papers receiving 503 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Shaoya Guan	390	213	168	99	55	15	517
Kui Wang	359 0.9×	88 0.4×	83 0.5×	48 0.5×	63 1.1×	19	476
Ge Fang	396 1.0×	98 0.5×	102 0.6×	47 0.5×	80 1.5×	27	549
Jérémie Dequidt	319 0.8×	145 0.7×	134 0.8×	109 1.1×	60 1.1×	36	529
Angela Faragasso	436 1.1×	173 0.8×	118 0.7×	73 0.7×	64 1.2×	27	528
Yangxin Xu	232 0.6×	135 0.6×	75 0.4×	107 1.1×	38 0.7×	24	539
Jiewen Lai	407 1.0×	206 1.0×	162 1.0×	40 0.4×	55 1.0×	38	526
Junghwan Back	407 1.0×	202 0.9×	120 0.7×	24 0.2×	46 0.8×	27	505
B. H. Brown	390 1.0×	154 0.7×	220 1.3×	34 0.3×	35 0.6×	18	606
Jienan Ding	456 1.2×	160 0.8×	96 0.6×	68 0.7×	42 0.8×	14	583
Bruno Scaglioni	292 0.7×	82 0.4×	85 0.5×	93 0.9×	95 1.7×	27	517

Countries citing papers authored by Shaoya Guan

Since Specialization

Citations

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

Fields of papers citing papers by Shaoya Guan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shaoya Guan

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

All Works

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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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