Yang Han

71 papers receiving 792 citations

Peers

Yang Han
Comparison fields: 5 of 125
  • Virology 68
  • Automotive Engineering 154
  • Internal Medicine 37
  • Infectious Diseases 106
  • Geriatrics and Gerontology 22
Replace Massimo Masi with:
Massimo Masi Italy
Simon Edwards United Kingdom
Heather Watson United States
Sheetal Agarwal India
Jing Zhao China
Andrew Galbraith Australia
Peter R. Chai United States
Xi Wang China
Mohammad Ebad Ur Rehman Pakistan
Long Zhang China
Yang Han relative to Massimo Masi Italy Massimo Masi's profile →
Citations per field
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Citations per year

Countries citing papers authored by Yang Han

Since Specialization
Citations

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

Fields of papers citing papers by Yang Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Yang Han, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Yang Han Line = papers co-authored together Yang Han links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 79 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202286
2 201781
3 202174
4
Distinctive rheumatic manifestations in 98 patients with human immunodeficiency virus infection in China.
200735
5 201932
6
Rapid loss of both CD4+ and CD8+ T lymphocyte subsets during the acute phase of severe acute respiratory syndrome.
200332
7 201331
8 202129
9 201226
10 201224
11 202022
12 202217
13
[Dynamic changes of T lymphocyte subsets in the long-term follow-up of severe acute respiratory syndrome patients].
200617
14 200615
15 201414
16 201614
17 200913
18 200613
19 201412
20 200912

About Yang Han

Yang Han is a scholar working on Infectious Diseases, Virology, Epidemiology, Surgery and Statistics and Probability, having authored 79 papers that have together received 810 indexed citations. Recurring topics across this work include HIV Research and Treatment (13 papers), Advanced Statistical Methods and Models (7 papers), Immune Cell Function and Interaction (7 papers), Pneumocystis jirovecii pneumonia detection and treatment (6 papers), HIV-related health complications and treatments (6 papers), Venous Thromboembolism Diagnosis and Management (5 papers), Statistical Methods in Clinical Trials (5 papers) and HIV/AIDS drug development and treatment (5 papers). The work is most often cited by research in Virology (68 citations), Automotive Engineering (154 citations), Internal Medicine (37 citations), Infectious Diseases (106 citations) and Geriatrics and Gerontology (22 citations). Yang Han has collaborated with scholars based in China, United Kingdom and Switzerland. Frequent co-authors include Taisheng Li, Zhenpo Wang, Zian Qin, Peng Liu, Yong Chen, Zhenyu Sun, Zhifeng Qiu, Peng Wang, Jing Xie and Pavol Bauer. Their work appears in journals such as JAIDS Journal of Acquired Immune Deficiency Syndromes, Journal of Applied Polymer Science, Journal of the Royal Statistical Society Series C (Applied Statistics), International Journal of Surgery and Scientific Reports.

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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