Siying Li

52 total papers · 792 total citations
37 papers, 502 citations indexed

About

Siying Li is a scholar working on Oncology, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Siying Li has authored 37 papers receiving a total of 502 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Oncology, 6 papers in Molecular Biology and 6 papers in Artificial Intelligence. Recurrent topics in Siying Li's work include AI in cancer detection (6 papers), Colorectal Cancer Screening and Detection (5 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Siying Li is often cited by papers focused on AI in cancer detection (6 papers), Colorectal Cancer Screening and Detection (5 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Siying Li collaborates with scholars based in China, United States and Canada. Siying Li's co-authors include Guanghui Yue, Tianfu Wang, Tianwei Zhou, Ming Hong, Jinke Li, Mohammed M. Almutairi, Runmin Cong, Baiying Lei, Jiaxin Yang and Tingting Zhao and has published in prestigious journals such as SHILAP Revista de lepidopterología, Environmental Science & Technology and NeuroImage.

In The Last Decade

Siying Li

30 papers receiving 490 citations

Author Peers

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

Author						Papers	Cites
Siying Li	110	97	89	68	63	37	502
Weimin Huang	51 0.5×	86 0.9×	52 0.6×	47 0.7×	36 0.6×	60	560
Şafak Şahin	84 0.8×	100 1.0×	75 0.8×	24 0.4×	68 1.1×	45	599
Samir Jabari	48 0.4×	132 1.4×	129 1.4×	21 0.3×	36 0.6×	43	550
Gehad El Ashal	70 0.6×	133 1.4×	42 0.5×	28 0.4×	16 0.3×	15	583
Alejandro Cohen	36 0.3×	68 0.7×	72 0.8×	17 0.3×	45 0.7×	54	581
Mao Xie	49 0.4×	169 1.7×	43 0.5×	82 1.2×	32 0.5×	44	614
Yuheng Chen	88 0.8×	85 0.9×	173 1.9×	24 0.4×	52 0.8×	35	476
Sanghamitra Satpathi	28 0.3×	80 0.8×	55 0.6×	131 1.9×	160 2.5×	26	496
Paul Liu	42 0.4×	211 2.2×	54 0.6×	26 0.4×	41 0.7×	39	606
Lingfang Li	64 0.6×	139 1.4×	84 0.9×	41 0.6×	12 0.2×	30	466

Countries citing papers authored by Siying Li

Since Specialization

Citations

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

Fields of papers citing papers by Siying Li

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Siying Li

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