Han Yuan

1.1k total citations
55 papers, 626 citations indexed

About

Han Yuan is a scholar working on Artificial Intelligence, Health Information Management and Health Informatics. According to data from OpenAlex, Han Yuan has authored 55 papers receiving a total of 626 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Artificial Intelligence, 9 papers in Health Information Management and 7 papers in Health Informatics. Recurrent topics in Han Yuan's work include Machine Learning in Healthcare (17 papers), Artificial Intelligence in Healthcare and Education (7 papers) and Artificial Intelligence in Healthcare (5 papers). Han Yuan is often cited by papers focused on Machine Learning in Healthcare (17 papers), Artificial Intelligence in Healthcare and Education (7 papers) and Artificial Intelligence in Healthcare (5 papers). Han Yuan collaborates with scholars based in Singapore, China and United States. Han Yuan's co-authors include Feng Xie, Nan Liu, Marcus Eng Hock Ong, Yilin Ning, Bibhas Chakraborty, Liang Zhao, Keping Yu, Shahid Mumtaz, Hristo S. Paskov and Christina S. Leslie and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Automatica.

In The Last Decade

Han Yuan

48 papers receiving 608 citations

Peers

Han Yuan
Comparison fields: 5 of 138
  • Artificial Intelligence 206
  • Molecular Biology 91
  • Electrical and Electronic Engineering 74
  • Health Information Management 69
  • Radiology, Nuclear Medicine and Imaging 65
Replace Indro Spinelli with:
Indro Spinelli Italy
Md. Sarwar Kamal Bangladesh
Mohd Khaled Yousef Shambour Saudi Arabia
Haohui Lu Australia
Chao Yan United States
Lucy Hutchinson Switzerland
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Muhannad A. Abu‐Hashem Saudi Arabia
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Indro Spinelli Italy View profile →
Citations per field, relative to Han Yuan
Han Yuan · 1×
Citations per year, relative to Han Yuan
Han Yuan · 1×

Countries citing papers authored by Han Yuan

Since Specialization
Citations

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

Fields of papers citing papers by Han Yuan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Han Yuan

This figure shows the co-authorship network connecting the top 25 collaborators of Han Yuan. A scholar is included among the top collaborators of Han Yuan 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 Han Yuan. Han Yuan 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 7
2 1
3 3
4 0
5 3
6 4
7 11
8 0
9 5
10 5
11 15
12 6
13 1
14 14
15 1
16 73
17 27
18 2
19 17
20
Thinking on the Supervision and Management of Stock Market in China
0

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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