Nan Mei

851 citations
24 papers · 546 indexed · 1 hit paper · h-index 8
Topics
Radiomics and Machine Learning in Medical Imaging (7 papers)COVID-19 diagnosis using AI (6 papers)MRI in cancer diagnosis (5 papers)

In The Last Decade

Nan Mei

21 papers receiving 537 citations

Hit Papers

Cerebral Micro-Structural Changes in COVID-19 Patients – ...20202026202220242020100200300400

Peers

Nan Mei
Comparison fields: 5 of 79
  • Neurology 375
  • Infectious Diseases 150
  • Clinical Psychology 119
  • Radiology, Nuclear Medicine and Imaging 117
  • Critical Care and Intensive Care Medicine 102
Replace Anling Xiao with:
Anling Xiao China
Yajing Zhao China
Jacques‐Yves Campion France
Anna S. Nordvig United States
Mathieu Queneau France
Hu Guo China
Akram A. Hosseini United Kingdom
Vivian A. Guedes United States
Ruairi Connolly Ireland
José Antonio Arias Navalón Spain
Nan Mei relative to Anling Xiao China Anling Xiao's profile →
Citations per field
00.5×1.5×
Anling Xiao · 1×
Citations per year

Countries citing papers authored by Nan Mei

Since Specialization
Citations

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

Fields of papers citing papers by Nan Mei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nan Mei

This figure shows the co-authorship network connecting the top 25 collaborators of Nan Mei. A scholar is included among the top collaborators of Nan Mei 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 Nan Mei. Nan Mei 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
#WorkIndexed citations
1 15
2 8
3 0
4 6
5 2
6 2
7 3
8 1
9 8
10 3
11 7
12 10
13 10
14 4
15 20
16
Cerebral Micro-Structural Changes in COVID-19 Patients – An MRI-based 3-month Follow-up Studybreakdown →
417
17 2
18 16
19 1
20
[Activity of mechanoreceptors of the peritoneum and intestine in the splanchnic region. Microphysiologic study at the level of the spinal ganglia in cats].
2

About Nan Mei

Nan Mei is a scholar working on Radiology, Nuclear Medicine and Imaging, Neurology and Genetics, having authored 24 papers that have together received 546 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (7 papers), COVID-19 diagnosis using AI (6 papers) and MRI in cancer diagnosis (5 papers). The work is most often cited by research in Neurology (375 citations), Critical Care and Intensive Care Medicine (102 citations) and Neurology (95 citations). Nan Mei has collaborated with scholars based in China, United Kingdom and Australia. Frequent co-authors include Bo Yin, Xuanxuan Li, Yiping Lu, Yajing Zhao, Anling Xiao, Dongdong Wang, Daoying Geng, Chu‐Chung Huang, Pu‐Yeh Wu and Tianye Jia. Their work appears in journals such as Journal of Hazardous Materials, Journal of Magnetic Resonance Imaging and European Radiology.

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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