Lituan Wang
Impact in
- Health Informatics top 10%
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- Advanced Neural Network Applications
- Medical Image Segmentation Techniques
- Digital Imaging for Blood Diseases
Papers in
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- Advanced Neural Network Applications 6
- Digital Imaging for Blood Diseases 3
- Image Retrieval and Classification Techniques 2
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- AI in cancer detection 7
- Domain Adaptation and Few-Shot Learning 4
- Co-authors
- Lei Zhang (19 shared papers)Y K Zhang (6 shared papers)Xiaofeng Qi (2 shared papers)Yi Zhang (1 shared paper)Yuchen Yuan (2 shared papers)Haiying Huang (2 shared papers)Zizhou Wang (5 shared papers)Xin Shu (4 shared papers)
In The Last Decade
Lituan Wang
24 papers receiving 535 citations
Peers
Comparison fields: 5 of 78
- Health Informatics 18
- Computer Vision and Pattern Recognition 222
- Radiology, Nuclear Medicine and Imaging 204
- Artificial Intelligence 257
- Neurology 43
Countries citing papers authored by Lituan Wang
This map shows the geographic impact of Lituan 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 Lituan Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lituan Wang more than expected).
Fields of papers citing papers by Lituan Wang
This network shows the impact of papers produced by Lituan 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 Lituan Wang. The network helps show where Lituan Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Lituan Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 120 | |
| 2 | 2021 | 93 | |
| 3 | 2017 | 79 | |
| 4 | 2018 | 45 | |
| 5 | 2021 | 42 | |
| 6 | 2023 | 38 | |
| 7 | 2021 | 32 | |
| 8 | 2021 | 16 | |
| 9 | 2017 | 14 | |
| 10 | 2019 | 13 | |
| 11 | 2024 | 12 | |
| 12 | 2023 | 10 | |
| 13 | 2022 | 9 | |
| 14 | 2023 | 8 | |
| 15 | 2023 | 5 | |
| 16 | 2021 | 5 | |
| 17 | 2022 | 2 | |
| 18 | 2022 | 2 | |
| 19 | 2021 | 2 | |
| 20 | 2023 | 1 |
About Lituan Wang
Lituan Wang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Neurology and Ophthalmology, having authored 24 papers that have together received 552 indexed citations. Recurring topics across this work include AI in cancer detection (7 papers), Advanced Neural Network Applications (6 papers), Domain Adaptation and Few-Shot Learning (4 papers), Digital Imaging for Blood Diseases (3 papers), Retinal Imaging and Analysis (3 papers), Cutaneous Melanoma Detection and Management (2 papers), Image Retrieval and Classification Techniques (2 papers) and COVID-19 diagnosis using AI (2 papers). The work is most often cited by research in Health Informatics (18 citations), Computer Vision and Pattern Recognition (222 citations), Radiology, Nuclear Medicine and Imaging (204 citations), Artificial Intelligence (257 citations) and Neurology (43 citations). Lituan Wang has collaborated with scholars based in China and Singapore. Frequent co-authors include Lei Zhang, Y K Zhang, Xiaofeng Qi, Yi Zhang, Yuchen Yuan, Haiying Huang, Zizhou Wang, Xin Shu, Rui Cai Gu and Yan Wang. Their work appears in journals such as IEEE Transactions on Cognitive and Developmental Systems, Knowledge-Based Systems, Medical Image Analysis, IEEE Journal of Biomedical and Health Informatics and International Journal of Computer Assisted Radiology and Surgery.
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.