Xun Yao

41 total papers · 1.2k total citations
29 papers, 925 citations indexed

About

Xun Yao is a scholar working on Oncology, Molecular Biology and Pathology and Forensic Medicine. According to data from OpenAlex, Xun Yao has authored 29 papers receiving a total of 925 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Oncology, 6 papers in Molecular Biology and 6 papers in Pathology and Forensic Medicine. Recurrent topics in Xun Yao's work include Colorectal Cancer Surgical Treatments (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Gastric Cancer Management and Outcomes (4 papers). Xun Yao is often cited by papers focused on Colorectal Cancer Surgical Treatments (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Gastric Cancer Management and Outcomes (4 papers). Xun Yao collaborates with scholars based in China, United Kingdom and Italy. Xun Yao's co-authors include Liang Du, Mao‐Ling Wei, Yong Zhou, Xin Sun, Joey S.W. Kwong, Antonio Nicolucci, Yajie Dong, Haoming Tian, Sheyu Li and Yuan Wu and has published in prestigious journals such as Ophthalmology, International Journal of Cancer and European Journal of Cancer.

In The Last Decade

Xun Yao

28 papers receiving 899 citations

Author Peers

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

Author						Papers	Cites
Xun Yao	280	194	189	178	175	29	925
Dale S. Hardy	128 0.5×	75 0.4×	46 0.2×	270 1.5×	98 0.6×	27	988
Jian Lu	85 0.3×	95 0.5×	113 0.6×	217 1.2×	309 1.8×	54	1.2k
Joana C. Vasconcelos	76 0.3×	61 0.3×	182 1.0×	78 0.4×	75 0.4×	34	897
Melissa M. Moore	97 0.3×	38 0.2×	91 0.5×	534 3.0×	233 1.3×	53	1.2k
Corran Roberts	65 0.2×	119 0.6×	165 0.9×	91 0.5×	64 0.4×	18	918
Eunjoo Jeon	194 0.7×	60 0.3×	60 0.3×	184 1.0×	499 2.9×	37	1.2k
Sarah L. Hulin-Curtis	87 0.3×	66 0.3×	91 0.5×	163 0.9×	170 1.0×	22	927
Yunji Hwang	41 0.1×	222 1.1×	136 0.7×	170 1.0×	131 0.7×	30	816
Jenna Bollyky	80 0.3×	294 1.5×	269 1.4×	58 0.3×	207 1.2×	31	1.0k
Yiduo Zhang	155 0.6×	276 1.4×	65 0.3×	162 0.9×	96 0.5×	22	1.1k

Countries citing papers authored by Xun Yao

Since Specialization

Citations

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

Fields of papers citing papers by Xun Yao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xun Yao

This figure shows the co-authorship network connecting the top 25 collaborators of Xun Yao. A scholar is included among the top collaborators of Xun Yao 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 Xun Yao. Xun Yao 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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