Zhenwei Shi

110 total papers · 2.4k total citations
65 papers, 1.5k citations indexed

About

Zhenwei Shi is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Zhenwei Shi has authored 65 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Radiology, Nuclear Medicine and Imaging, 18 papers in Artificial Intelligence and 15 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Zhenwei Shi's work include Radiomics and Machine Learning in Medical Imaging (42 papers), AI in cancer detection (18 papers) and Lung Cancer Diagnosis and Treatment (10 papers). Zhenwei Shi is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (42 papers), AI in cancer detection (18 papers) and Lung Cancer Diagnosis and Treatment (10 papers). Zhenwei Shi collaborates with scholars based in China, Netherlands and United States. Zhenwei Shi's co-authors include Leonard Wee, André Dekker, Zaiyi Liu, Chu Han, Alberto Traverso, Yanfen Cui, Tal V. Murthy, Joshua LaBaer, Zeyan Xu and Petros Kalendralis and has published in prestigious journals such as PLoS ONE, Radiology and Genome Research.

In The Last Decade

Zhenwei Shi

58 papers receiving 1.5k citations

Hit Papers

MRI-based Quantification ... 2022 2026 2023 2024 2023 2022 2023 25 50 75 100

Author Peers

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

Author Last Decade Papers Cites
Zhenwei Shi 790 394 365 291 208 65 1.5k
Longzhong Liu 501 0.6× 234 0.6× 409 1.1× 143 0.5× 177 0.9× 46 1.3k
Shidan Wang 545 0.7× 308 0.8× 552 1.5× 369 1.3× 332 1.6× 45 1.5k
Ming Fan 921 1.2× 382 1.0× 464 1.3× 166 0.6× 123 0.6× 79 1.6k
Shichong Zhou 806 1.0× 152 0.4× 592 1.6× 127 0.4× 85 0.4× 63 1.4k
Daisuke Komura 399 0.5× 433 1.1× 505 1.4× 171 0.6× 304 1.5× 61 1.5k
Georgios Z. Papadakis 582 0.7× 123 0.3× 251 0.7× 346 1.2× 311 1.5× 83 1.6k
António Polónia 806 1.0× 394 1.0× 969 2.7× 138 0.5× 363 1.7× 49 1.7k
Jana Lipková 650 0.8× 219 0.6× 545 1.5× 116 0.4× 131 0.6× 30 1.4k
Carlo Russo 477 0.6× 333 0.8× 158 0.4× 68 0.2× 191 0.9× 79 1.7k
Guangzhi Ma 421 0.5× 119 0.3× 251 0.7× 414 1.4× 285 1.4× 78 1.2k

Countries citing papers authored by Zhenwei Shi

Since Specialization
Citations

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

Fields of papers citing papers by Zhenwei Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhenwei Shi

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