Fang Wu

37 papers receiving 790 citations

Peers

Fang Wu
Comparison fields: 5 of 107
  • Pulmonary and Respiratory Medicine 268
  • Neurology 119
  • Epidemiology 236
  • Genetics 165
  • Complementary and alternative medicine 43
Replace Xiangyu Chen with:
Xiangyu Chen China
Andy Goren United States
Xiaoqi Wang China
Shu Wan China
Carolina Kymie Vasques Nonaka Brazil
Paul Kaplan United States
Jayne S. Reuben United States
George Androutsos Greece
Sidharth Sonthalia India
Fang Wu relative to Xiangyu Chen China Xiangyu Chen's profile →
Citations per field
00.5×3.9×
Xiangyu Chen · 1×
Citations per year

Countries citing papers authored by Fang Wu

Since Specialization
Citations

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

Fields of papers citing papers by Fang Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1997102
2 201279
3 199778
4 201865
5 201861
6 201842
7 200835
8 202132
9 201631
10 202331
11 201826
12 202121
13 202418
14 200018
15 201718
16 201915
17 201913
18 202012
19 202111
20
Clinical significance of pain in patients with chronic heart failure.
201211

About Fang Wu

Fang Wu is a scholar working on Pulmonary and Respiratory Medicine, Epidemiology, Neurology, Cardiology and Cardiovascular Medicine and Molecular Biology, having authored 42 papers that have together received 803 indexed citations. Recurring topics across this work include Cerebrovascular and Carotid Artery Diseases (12 papers), Acute Ischemic Stroke Management (8 papers), Intracranial Aneurysms: Treatment and Complications (5 papers), Moyamoya disease diagnosis and treatment (3 papers), Ion channel regulation and function (3 papers), Venomous Animal Envenomation and Studies (3 papers), Pharmacovigilance and Adverse Drug Reactions (2 papers) and Healthcare Policy and Management (2 papers). The work is most often cited by research in Pulmonary and Respiratory Medicine (268 citations), Neurology (119 citations), Epidemiology (236 citations), Genetics (165 citations) and Complementary and alternative medicine (43 citations). Fang Wu has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Pierre Escoubas, Qi Yang, Terumi Nakajima, Régine Romi‐Lebrun, Miki Hisada, Bruno Lebrun, Marie‐France Martin‐Eauclaire, Zhaoyang Fan, Debiao Li and Lan Tang. Their work appears in journals such as Journal of the American Heart Association, International Journal of Environmental Research and Public Health, European Radiology, Annals of Palliative Medicine and Theranostics.

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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