Xin Tian
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Computer Vision and Pattern Recognition top 10%
- Electrical and Electronic Engineering
- Obstetrics and Gynecology top 10%
- Co-authors
- Huiling ChenXuehua ZhaoYing HuangLufeng HuZhennao CaiXiang ZhangXianqin WangHui Huang
- Topics
- Video Surveillance and Tracking Methods (5 papers)Radiomics and Machine Learning in Medical Imaging (4 papers)Endometrial and Cervical Cancer Treatments (4 papers)
In The Last Decade
Xin Tian
17 papers receiving 715 citations
Hit Papers
Peers
Comparison fields: 5 of 122
- Artificial Intelligence 329
- Radiology, Nuclear Medicine and Imaging 140
- Computer Vision and Pattern Recognition 99
- Electrical and Electronic Engineering 71
- Obstetrics and Gynecology 69
Countries citing papers authored by Xin Tian
This map shows the geographic impact of Xin Tian'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 Xin Tian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xin Tian more than expected).
Fields of papers citing papers by Xin Tian
This network shows the impact of papers produced by Xin Tian. 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 Xin Tian. The network helps show where Xin Tian may publish in the future.
Co-authorship network of co-authors of Xin Tian
This figure shows the co-authorship network connecting the top 25 collaborators of Xin Tian. A scholar is included among the top collaborators of Xin Tian 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 Xin Tian. Xin Tian 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 | 8 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 24 | |
| 8 | 7 | |
| 9 | 7 | |
| 10 | 6 | |
| 11 | 1 | |
| 12 | 25 | |
| 13 | 79 | |
| 14 | 1 | |
| 15 | Chaos enhanced grey wolf optimization wrapped ELM for diagnosis of paraquat-poisoned patientsbreakdown → | 278 |
| 16 | 249 | |
| 17 | 13 | |
| 18 | 9 | |
| 19 | 6 | |
| 20 | Application of Scale Invariant Feature Transformation to SAR Imagery Registration | 7 |
About Xin Tian
Xin Tian is a scholar working on Obstetrics and Gynecology, Computer Vision and Pattern Recognition and Automotive Engineering, having authored 20 papers that have together received 726 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Endometrial and Cervical Cancer Treatments (4 papers). The work is most often cited by research in Artificial Intelligence (329 citations), Obstetrics and Gynecology (69 citations) and Radiology, Nuclear Medicine and Imaging (140 citations). Xin Tian has collaborated with scholars based in China, Canada and Taiwan. Frequent co-authors include Huiling Chen, Xuehua Zhao, Ying Huang, Lufeng Hu, Zhennao Cai, Xiang Zhang, Xianqin Wang, Hui Huang, Wenbin Liu and Changfei Tong. Their work appears in journals such as Expert Systems with Applications, IEEE Access and Energy.
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.