Ling Fu

900 citations
19 papers · 715 indexed · h-index 11

Impact in

Papers in

Ling Fu

18 papers receiving 673 citations

Peers

Ling Fu
Comparison fields: 5 of 94
  • Complementary and alternative medicine 69
  • Cancer Research 114
  • Pharmacology 58
  • Anesthesiology and Pain Medicine 31
  • Molecular Biology 364
Replace Masayuki Azuma with:
Masayuki Azuma Japan
Meina Zhao China
Qi Zhao China
Allison M. Hunter United States
Yuhong Zhang China
Mei Xue China
Renê Donizeti Ribeiro de Oliveira Brazil
Kang-Yun Lee Taiwan
J.R. Marsden United Kingdom
Ling Fu relative to Masayuki Azuma Japan Masayuki Azuma's profile →
Citations per field
00.5×7.7×
Masayuki Azuma · 1×
Citations per year

Countries citing papers authored by Ling Fu

Since Specialization
Citations

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

Fields of papers citing papers by Ling Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

19 of 19 papers shown
#Work
1 202210
2 202222
3 20225
4 20217
5 202148
6 202021
7 202011
8 202039
9 20206
10 201929
11 20177
12 20161
13 201476
14 20127
15 201142
16 20116
17 200596
18 2005282
19
Why our Western-trained doctors should learn traditional Chinese medicine.
20030

About Ling Fu

Ling Fu is a scholar working on Complementary and alternative medicine, Hematology, Developmental Neuroscience, Periodontics and Rheumatology, having authored 19 papers that have together received 715 indexed citations. Recurring topics across this work include Natural Compounds in Disease Treatment (5 papers), Autoimmune and Inflammatory Disorders Research (3 papers), Palliative Care and End-of-Life Issues (3 papers), Natural product bioactivities and synthesis (2 papers), Patient Dignity and Privacy (2 papers), Angiogenesis and VEGF in Cancer (2 papers), Rheumatoid Arthritis Research and Therapies (2 papers) and Traditional Chinese Medicine Studies (2 papers). The work is most often cited by research in Complementary and alternative medicine (69 citations), Cancer Research (114 citations), Pharmacology (58 citations), Anesthesiology and Pain Medicine (31 citations) and Molecular Biology (364 citations). Ling Fu has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Hans‐Peter Gerber, Franklin Peale, Xiumin Wu, Wei‐Ching Liang, Napoleone Ferrara, Ajay K. Malik, Y. Gloria Meng, Germaine Fuh, Chingwei V. Lee and Johnny Gutierrez. Their work appears in journals such as Biomedicine & Pharmacotherapy, Molecular Cancer Therapeutics, International Journal of Environmental Research and Public Health, Journal of Palliative Medicine and The Journal of Pathology.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026