Zhuoshi Wei

524 citations
18 papers · 225 · h-index 7

Impact in

Papers in

Zhuoshi Wei

17 papers receiving 219 citations

Peers

Zhuoshi Wei
Comparison fields: 5 of 42
  • Signal Processing 126
  • Computer Vision and Pattern Recognition 98
  • Safety Research 37
  • Information Systems 61
  • Health Informatics 3
Replace Dong Seop Kim with:
Dong Seop Kim South Korea
Martin Aastrup Olsen Germany
Akshay Girdhar India
Luke Nicholas Darlow South Africa
Christof Kauba Austria
Umarani Jayaraman India
Akanksha Joshi India
Shankar Bhausaheb Nikam India
Bernhard Prommegger Austria
Jascha Kolberg Germany
Zhuoshi Wei relative to Dong Seop Kim South Korea Dong Seop Kim's profile →
Citations per field
00.5×1.5×2.1×
Dong Seop Kim · 1×
Citations per year

Countries citing papers authored by Zhuoshi Wei

Since Specialization
Citations

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

Fields of papers citing papers by Zhuoshi Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Zhuoshi Wei, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Zhuoshi Wei Line = papers co-authored together Zhuoshi Wei links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 200889
2 201737
3 200831
4 20149
5 20099
6 20168
7 20167
8 20126
9 20136
10 20086
11 20135
12 20125
13 20133
14 20121
15 20111
16 20101
17 20121
18 20120

About Zhuoshi Wei

Zhuoshi Wei is a scholar working on Computer Vision and Pattern Recognition, Oncology, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Signal Processing, having authored 18 papers that have together received 225 indexed citations. Recurring topics across this work include Colorectal Cancer Screening and Detection (7 papers), Medical Image Segmentation Techniques (6 papers), Biometric Identification and Security (4 papers), AI in cancer detection (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Image Retrieval and Classification Techniques (3 papers), COVID-19 diagnosis using AI (3 papers) and Forensic and Genetic Research (2 papers). The work is most often cited by research in Signal Processing (126 citations), Computer Vision and Pattern Recognition (98 citations), Safety Research (37 citations), Information Systems (61 citations) and Health Informatics (3 citations). Zhuoshi Wei has collaborated with scholars based in United States, China and Thailand. Frequent co-authors include Zhenan Sun, Tieniu Tan, Xianchao Qiu, Ronald M. Summers, Le Lü, Evrim Türkbey, Lauren Kim, Nicholas Petrick, Shijun Wang and Jiamin Liu. Their work appears in journals such as Medical Physics, Medical Image Analysis, American Journal of Roentgenology, Lecture notes in computer science and Proceedings - International Conference on Pattern Recognition.

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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