Wanli Liu
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Computer Vision and Pattern Recognition top 5%
- Epidemiology
- Biomedical Engineering
- Co-authors
- Hongzan SunMarcin GrzegorzekChen LiHaoyuan ChenWeiming HuMd Mamunur RahamanChanghao SunXiaoyan Li
- Topics
- AI in cancer detection (6 papers)Synthetic Aperture Radar (SAR) Applications and Techniques (5 papers)Radiomics and Machine Learning in Medical Imaging (4 papers)
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionRadiology, Nuclear Medicine and Imaging
- Partner nations
- ChinaGermanyUnited States
In The Last Decade
Wanli Liu
22 papers receiving 617 citations
Hit Papers
Peers
Comparison fields: 5 of 88
- Artificial Intelligence 378
- Radiology, Nuclear Medicine and Imaging 209
- Computer Vision and Pattern Recognition 202
- Epidemiology 67
- Biomedical Engineering 61
Countries citing papers authored by Wanli Liu
This map shows the geographic impact of Wanli Liu'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 Wanli Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wanli Liu more than expected).
Fields of papers citing papers by Wanli Liu
This network shows the impact of papers produced by Wanli Liu. 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 Wanli Liu. The network helps show where Wanli Liu may publish in the future.
Co-authorship network of co-authors of Wanli Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Wanli Liu. A scholar is included among the top collaborators of Wanli Liu 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 Wanli Liu. Wanli Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 38 | |
| 3 | 13 | |
| 4 | 1 | |
| 5 | 101 | |
| 6 | 15 | |
| 7 | 2 | |
| 8 | GasHis-Transformer: A multi-scale visual transformer approach for gastric histopathological image detectionbreakdown → | 177 |
| 9 | 54 | |
| 10 | 1 | |
| 11 | 34 | |
| 12 | 5 | |
| 13 | Factuality Classification Using the Pre-trained Language Representation Model BERT. | 5 |
| 14 | A BERT-based Approach for Automatic Humor Detection and Scoring. | 20 |
| 15 | 2 | |
| 16 | 14 | |
| 17 | 1 | |
| 18 | 10 | |
| 19 | Enhancing LTP-Driven Cache Management Using Reuse Distance Information | 2 |
| 20 | General Bayes Diagnosis Method | 1 |
About Wanli Liu
Wanli Liu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Hardware and Architecture, having authored 23 papers that have together received 632 indexed citations. Recurring topics across this work include AI in cancer detection (6 papers), Synthetic Aperture Radar (SAR) Applications and Techniques (5 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). The work is most often cited by research in Artificial Intelligence (378 citations), Computer Vision and Pattern Recognition (202 citations) and Radiology, Nuclear Medicine and Imaging (209 citations). Wanli Liu has collaborated with scholars based in China, Germany and United States. Frequent co-authors include Hongzan Sun, Marcin Grzegorzek, Chen Li, Haoyuan Chen, Weiming Hu, Md Mamunur Rahaman, Changhao Sun, Xiaoyan Li, Yixin Li and Xiangchen Wu. Their work appears in journals such as Scientific Reports, Sensors and 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.