Xiaoli Qin

416 total citations
22 papers, 293 citations indexed

About

Xiaoli Qin is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Xiaoli Qin has authored 22 papers receiving a total of 293 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 4 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Molecular Biology. Recurrent topics in Xiaoli Qin's work include COVID-19 diagnosis using AI (4 papers), AI in cancer detection (3 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). Xiaoli Qin is often cited by papers focused on COVID-19 diagnosis using AI (4 papers), AI in cancer detection (3 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). Xiaoli Qin collaborates with scholars based in China, Canada and United States. Xiaoli Qin's co-authors include Qi Zhao, Hongbo Zhao, Wenquan Feng, Francis M. Bui, Anh Dinh, Zhu Han, Wenquan Feng, Yuping Li, Wei-Hong Liang and Qian Jiang and has published in prestigious journals such as Cancer Research, Scientific Reports and IEEE Access.

In The Last Decade

Xiaoli Qin

19 papers receiving 284 citations

Peers

Xiaoli Qin
Comparison fields: 5 of 71
  • Automotive Engineering 165
  • Electrical and Electronic Engineering 136
  • Safety, Risk, Reliability and Quality 67
  • Control and Systems Engineering 49
  • Artificial Intelligence 33
Replace Weicong Hong with:
Weicong Hong China
Toshihiro Wada Japan
Mohammad Mohammadi Iran
Safa Meraghni France
Khaled Benaggoune Algeria
Wenxue Liu China
Nuria Caballé Spain
Jaeyoung Moon South Korea
Weiting Xu China
Weicong Hong China View profile →
Citations per field, relative to Xiaoli Qin
Xiaoli Qin · 1×
Citations per year, relative to Xiaoli Qin
Xiaoli Qin · 1×

Countries citing papers authored by Xiaoli Qin

Since Specialization
Citations

This map shows the geographic impact of Xiaoli Qin'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 Xiaoli Qin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoli Qin more than expected).

Fields of papers citing papers by Xiaoli Qin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiaoli Qin. 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 Xiaoli Qin. The network helps show where Xiaoli Qin may publish in the future.

Co-authorship network of co-authors of Xiaoli Qin

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaoli Qin. A scholar is included among the top collaborators of Xiaoli Qin 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 Xiaoli Qin. Xiaoli Qin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 2
3 4
4 2
5 2
6 3
7 4
8 5
9 15
10 12
11 9
12 23
13 2
14 1
15 159
16 22
17 2
18 5
19 19
20
Investigation of Key Technology Based on the Embedded System of Boa
1

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.

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