Nan Lu

463 citations
31 papers · 302 · h-index 9

Impact in

Papers in

Nan Lu

29 papers receiving 296 citations

Peers

Nan Lu
Comparison fields: 5 of 60
  • Cardiology and Cardiovascular Medicine 83
  • Orthopedics and Sports Medicine 32
  • Oncology 42
  • Obstetrics and Gynecology 11
  • Health Informatics 2
Replace Chiara Cappelletto with:
Chiara Cappelletto Italy
Anouk L. M. Eikendal Netherlands
Jianzhong Xian China
Anne Sophie Bargnoux France
Pedro Antunes Portugal
Dee Pei Taiwan
Tae Hun Kim South Korea
Qinmei Xiong China
Yawei Wu China
Diego Colonna Italy
Nan Lu relative to Chiara Cappelletto Italy Chiara Cappelletto's profile →
Citations per field
00.5×11×
Chiara Cappelletto · 1×
Citations per year

Countries citing papers authored by Nan Lu

Since Specialization
Citations

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

Fields of papers citing papers by Nan Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201955
2 201945
3 201233
4 201422
5 201820
6 201616
7 201713
8 202211
9 201710
10 20218
11 20218
12 20198
13 20177
14 20176
15 20246
16 20196
17 20225
18 20195
19 20234
20 20192

About Nan Lu

Nan Lu is a scholar working on Cardiology and Cardiovascular Medicine, Endocrinology, Diabetes and Metabolism, Surgery, Pulmonary and Respiratory Medicine and Public Health, Environmental and Occupational Health, having authored 31 papers that have together received 302 indexed citations. Recurring topics across this work include Aortic Disease and Treatment Approaches (4 papers), Cardiac Health and Mental Health (3 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (3 papers), Biomarkers in Disease Mechanisms (2 papers), Heart rate and cardiovascular health (2 papers), Magnesium in Health and Disease (2 papers), Lipoproteins and Cardiovascular Health (2 papers) and Lipid metabolism and disorders (2 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (83 citations), Orthopedics and Sports Medicine (32 citations), Oncology (42 citations), Obstetrics and Gynecology (11 citations) and Health Informatics (2 citations). Nan Lu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Xuerui Tan, Jinxiu Zhu, Kan Sun, Yequn Chen, Tan Xu, Haojie Sun, Guang Ning, Minghui Yue, Jianfeng Ye and Dongfeng Chen. Their work appears in journals such as BMC Cardiovascular Disorders, Scientific Reports, BMC Gastroenterology, Medicine and BMC Medical Genomics.

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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