Hongyu Wang
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging top 5%
- Computer Vision and Pattern Recognition top 5%
- Experimental and Cognitive Psychology top 10%
- Electrical and Electronic Engineering
- Topics
- Radiomics and Machine Learning in Medical Imaging (13 papers)AI in cancer detection (10 papers)Medical Image Segmentation Techniques (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessFrontiers in Immunology
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Hongyu Wang
61 papers receiving 751 citations
Hit Papers
Peers
Comparison fields: 5 of 122
- Artificial Intelligence 251
- Radiology, Nuclear Medicine and Imaging 234
- Computer Vision and Pattern Recognition 174
- Experimental and Cognitive Psychology 106
- Electrical and Electronic Engineering 79
Countries citing papers authored by Hongyu Wang
This map shows the geographic impact of Hongyu Wang'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 Hongyu Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hongyu Wang more than expected).
Fields of papers citing papers by Hongyu Wang
This network shows the impact of papers produced by Hongyu Wang. 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 Hongyu Wang. The network helps show where Hongyu Wang may publish in the future.
Co-authorship network of co-authors of Hongyu Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Hongyu Wang. A scholar is included among the top collaborators of Hongyu Wang 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 Hongyu Wang. Hongyu Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 5 | |
| 8 | 1 | |
| 9 | 4 | |
| 10 | 3 | |
| 11 | 11 | |
| 12 | 0 | |
| 13 | 2 | |
| 14 | 29 | |
| 15 | 7 | |
| 16 | 1 | |
| 17 | 34 | |
| 18 | An application of Hadoop platform in cloud computing | 2 |
| 19 | S-Rough sets and its F-memory | 2 |
| 20 | Fractional Lower Order α-Stable Distribution and Issues in Its Applications | 0 |
About Hongyu Wang
Hongyu Wang is a scholar working on Nuclear Energy and Engineering, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, having authored 70 papers that have together received 779 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (13 papers), AI in cancer detection (10 papers) and Medical Image Segmentation Techniques (5 papers). The work is most often cited by research in Nuclear Energy and Engineering (6 citations), Health Informatics (15 citations) and Radiology, Nuclear Medicine and Imaging (234 citations). Hongyu Wang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Jun Feng, Songtao Ding, Shaohua Wan, Xiaoying Pan, Prayag Tiwari, Pekka Marttinen, Lei Cui, Lang He, Mingyue Niu and Rui Su. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Frontiers in Immunology.
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.