Aolun Li
Impact in
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- Brain Tumor Detection and Classification
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- Advanced Neural Network Applications
- Digital Imaging for Blood Diseases
- Medical Image Segmentation Techniques
Papers in
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- Medical Image Segmentation Techniques 2
- Advanced Neural Network Applications 2
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- AI in cancer detection 3
- Co-authors
- Long Yu (6 shared papers)Shengwei Tian (5 shared papers)Xiangzuo Huo (5 shared papers)Wendong Zhang (2 shared papers)Gang Sun (1 shared paper)Yan Wang (1 shared paper)Jun Long (1 shared paper)Wendong Zhang (1 shared paper)
- Journals
- Engineering Applications of Artificial Intelligence (1 paper)Complex & Intelligent Systems (1 paper)Biomedical Signal Processing and Control (1 paper)Expert Systems with Applications (1 paper)Medical & Biological Engineering & Computing (1 paper)
- Partner nations
- China
In The Last Decade
Aolun Li
5 papers receiving 186 citations
Aolun Li's Hit Papers
Peers
Comparison fields: 5 of 55
- Neurology 28
- Computer Vision and Pattern Recognition 69
- Radiology, Nuclear Medicine and Imaging 55
- Artificial Intelligence 70
- Computational Mathematics 1
Countries citing papers authored by Aolun Li
This map shows the geographic impact of Aolun 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 Aolun Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aolun Li more than expected).
Fields of papers citing papers by Aolun Li
This network shows the impact of papers produced by Aolun 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 Aolun Li. The network helps show where Aolun Li may publish in the future.
Co-authors
The 12 scholars most cited alongside Aolun Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | HiFuse: Hierarchical multi-scale feature fusion network for medical image classification Hit paper breakdown → | 2023 | 151 |
| 2 | 2022 | 15 | |
| 3 | 2023 | 10 | |
| 4 | 2023 | 8 | |
| 5 | 2024 | 2 | |
| 6 | 2025 | 0 |
About Aolun Li
Aolun Li is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Oncology, Neurology and Surgery, having authored 6 papers that have together received 186 indexed citations. Recurring topics across this work include AI in cancer detection (3 papers), Cutaneous Melanoma Detection and Management (2 papers), Medical Image Segmentation Techniques (2 papers), Brain Tumor Detection and Classification (2 papers), Advanced Neural Network Applications (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Nonmelanoma Skin Cancer Studies (1 paper) and Water Quality Monitoring Technologies (1 paper). The work is most often cited by research in Neurology (28 citations), Computer Vision and Pattern Recognition (69 citations), Radiology, Nuclear Medicine and Imaging (55 citations), Artificial Intelligence (70 citations) and Computational Mathematics (1 citation). Aolun Li has collaborated with scholars based in China. Frequent co-authors include Long Yu, Shengwei Tian, Xiangzuo Huo, Wendong Zhang, Gang Sun, Yan Wang, Jun Long, Wendong Zhang, Dezhi Zhang and Xiaojing Kang. Their work appears in journals such as Engineering Applications of Artificial Intelligence, Complex & Intelligent Systems, Biomedical Signal Processing and Control, Expert Systems with Applications and Medical & Biological Engineering & Computing.
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.