Minglei Li
- Radiology, Nuclear Medicine and Imaging top 5%
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Molecular Biology
- Ophthalmology top 5%
- Topics
- Radiomics and Machine Learning in Medical Imaging (8 papers)AI in cancer detection (8 papers)Pediatric Urology and Nephrology Studies (7 papers)
- Cited by
- Health InformaticsRadiology, Nuclear Medicine and ImagingComputer Vision and Pattern Recognition
- Journals
- SHILAP Revista de lepidopterologíaExpert Systems with ApplicationsIEEE Transactions on Medical Imaging
In The Last Decade
Minglei Li
47 papers receiving 890 citations
Hit Papers
Peers
Comparison fields: 5 of 133
- Radiology, Nuclear Medicine and Imaging 282
- Computer Vision and Pattern Recognition 246
- Artificial Intelligence 191
- Molecular Biology 114
- Ophthalmology 100
Countries citing papers authored by Minglei Li
This map shows the geographic impact of Minglei 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 Minglei Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Minglei Li more than expected).
Fields of papers citing papers by Minglei Li
This network shows the impact of papers produced by Minglei 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 Minglei Li. The network helps show where Minglei Li may publish in the future.
Co-authorship network of co-authors of Minglei Li
This figure shows the co-authorship network connecting the top 25 collaborators of Minglei Li. A scholar is included among the top collaborators of Minglei Li 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 Minglei Li. Minglei Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 3 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 7 | |
| 8 | 3 | |
| 9 | 2 | |
| 10 | 4 | |
| 11 | 12 | |
| 12 | 4 | |
| 13 | 8 | |
| 14 | 32 | |
| 15 | 7 | |
| 16 | A Parallel Hybrid Neural Network With Integration of Spatial and Temporal Features for Remaining Useful Life Prediction in Prognosticsbreakdown → | 85 |
| 17 | 0 | |
| 18 | Deep Learning Attention Mechanism in Medical Image Analysis: Basics and Beyondsbreakdown → | 152 |
| 19 | 194 | |
| 20 | 1 |
About Minglei Li
Minglei Li is a scholar working on Urology, Health Informatics and Radiology, Nuclear Medicine and Imaging, having authored 58 papers that have together received 907 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (8 papers), AI in cancer detection (8 papers) and Pediatric Urology and Nephrology Studies (7 papers). The work is most often cited by research in Health Informatics (20 citations), Radiology, Nuclear Medicine and Imaging (282 citations) and Computer Vision and Pattern Recognition (246 citations). Minglei Li has collaborated with scholars based in China, Norway and Spain. Frequent co-authors include Shen Yin, Yuchen Jiang, Xiang Li, Hao Luo, Jiusi Zhang, Pengfei Yan, Guanyi Li, Leopoldo G. Franquelo, José I. Leon and Jilun Tian. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Transactions on Medical Imaging.
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.