Sinan Wu

3.8k citations
28 papers · 324 · h-index 8

Impact in

Papers in

Sinan Wu

27 papers receiving 319 citations

Peers

Sinan Wu
Comparison fields: 5 of 92
  • Geriatrics and Gerontology 35
  • Internal Medicine 18
  • Health Information Management 20
  • Obstetrics and Gynecology 33
  • Physiology 96
Replace Teppei Suzuki with:
Teppei Suzuki Japan
Ting‐Ying Huang United States
Toshihiko Hasegawa Japan
José Francisco Kerr Saraiva Brazil
Rachel Bregman Brazil
Bernadet T. Santema Netherlands
Luisa C Brant Brazil
Joe Hollinghurst United Kingdom
Cynda Ann Johnson United States
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Citations per field
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Teppei Suzuki · 1×
Citations per year

Countries citing papers authored by Sinan Wu

Since Specialization
Citations

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

Fields of papers citing papers by Sinan Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Sinan Wu, 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 Sinan Wu Line = papers co-authored together Sinan Wu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201354
2 201753
3 201449
4 201642
5 201917
6
Anxiety and Depression in Patients with Chronic Obstructive Pulmonary Disease in China: Results from the China Pulmonary Health [CPH] Study
202115
7 202015
8 201814
9 20187
10 20226
11 20236
12 20236
13 20235
14 20165
15 20164
16 20224
17 20134
18 20223
19 20133
20 20232

About Sinan Wu

Sinan Wu is a scholar working on Pulmonary and Respiratory Medicine, Physiology, Molecular Biology, Surgery and Cardiology and Cardiovascular Medicine, having authored 28 papers that have together received 324 indexed citations. Recurring topics across this work include Chronic Obstructive Pulmonary Disease (COPD) Research (7 papers), Asthma and respiratory diseases (3 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (3 papers), Nutrition and Health in Aging (3 papers), Healthcare Policy and Management (2 papers), Healthcare cost, quality, practices (2 papers), Venous Thromboembolism Diagnosis and Management (2 papers) and Healthcare Systems and Reforms (2 papers). The work is most often cited by research in Geriatrics and Gerontology (35 citations), Internal Medicine (18 citations), Health Information Management (20 citations), Obstetrics and Gynecology (33 citations) and Physiology (96 citations). Sinan Wu has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Chen Wang, Keqin Rao, Qian Liu, Ping Zeng, Tiemei Zhang, Jing Pang, Huan Gong, Yiwen Han, Guohui Fan and Jianguo Zhu. Their work appears in journals such as CHEST Journal, Frontiers in Medicine, American Journal of Respiratory and Critical Care Medicine, Journal of Cancer 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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