Kai Nan

441 citations
16 papers · 309 · 1 hit paper · h-index 7

Impact in

Papers in

    • Clusterin in disease pathology 2
    • Bone health and treatments 2
    • Rheumatoid Arthritis Research and Therapies 2
    • Systemic Lupus Erythematosus Research 2

Kai Nan

15 papers receiving 306 citations

Kai Nan's Hit Papers

The Burden of Rheumatoid Arthritis: Findings from the 2019 Global Burden of Diseases Study and Forecasts for 2030 by Bayesian Age-Period-Cohort Analysis 2023 · 75 citations
750+1+2Years since publication255075

Peers

Kai Nan
Comparison fields: 5 of 85
  • Orthopedics and Sports Medicine 66
  • Rheumatology 49
  • Cancer Research 38
  • Neurology 19
  • Pathology and Forensic Medicine 36
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Kai Nan relative to Ia Pantsulaia Georgia Ia Pantsulaia's profile →
Citations per field
00.5×6.2×
Ia Pantsulaia · 1×
Citations per year

Countries citing papers authored by Kai Nan

Since Specialization
Citations

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

Fields of papers citing papers by Kai Nan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1 201776
2
The Burden of Rheumatoid Arthritis: Findings from the 2019 Global Burden of Diseases Study and Forecasts for 2030 by Bayesian Age-Period-Cohort Analysis
Hit paper breakdown →
202375
3 202156
4 201736
5 202118
6 20158
7 20237
8 20236
9 20246
10 20195
11 20244
12 20224
13 20243
14 20243
15 20232
16 20250

About Kai Nan

Kai Nan is a scholar working on Oncology, Rheumatology, Orthopedics and Sports Medicine, Infectious Diseases and Surgery, having authored 16 papers that have together received 309 indexed citations. Recurring topics across this work include Bone and Joint Diseases (3 papers), Tuberculosis Research and Epidemiology (2 papers), Clusterin in disease pathology (2 papers), Genetic Associations and Epidemiology (2 papers), Bone health and treatments (2 papers), Rheumatoid Arthritis Research and Therapies (2 papers), Biomarkers in Disease Mechanisms (2 papers) and Systemic Lupus Erythematosus Research (2 papers). The work is most often cited by research in Orthopedics and Sports Medicine (66 citations), Rheumatology (49 citations), Cancer Research (38 citations), Neurology (19 citations) and Pathology and Forensic Medicine (36 citations). Kai Nan has collaborated with scholars based in China. Frequent co-authors include Xiaoqian Dang, Lihong Fan, Kunzheng Wang, Jun‐Peng Pei, Zhaopu Jing, Jia Li, Jialin Liang, Guangyang Zhang, Leifeng Lv and Jianan Zhang. Their work appears in journals such as Frontiers in Endocrinology, Journal of Clinical Medicine, Lipids in Health and Disease, The Journal of Knee 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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