Di Ran

464 citations
19 papers · 308 · h-index 9

Impact in

Papers in

    • Osteoarthritis Treatment and Mechanisms 5
    • Statistical Methods in Clinical Trials 3
    • Advanced Causal Inference Techniques 2
    • Statistical Methods and Inference 2

Di Ran

17 papers receiving 304 citations

Peers

Di Ran
Comparison fields: 5 of 70
  • Rheumatology 53
  • Health, Toxicology and Mutagenesis 35
  • Nutrition and Dietetics 27
  • Molecular Biology 106
  • Cancer Research 21
Replace Shanshan Lin with:
Shanshan Lin China
Terence Ozolins Canada
Naya Huang China
Sarah C. Krzastek United States
Yufei Li China
Rulai Yang China
Sachiko Morioka Japan
Lyndsey Cruickshanks United Kingdom
Aradhana Upadhyay Australia
Mi Yeong Hwang South Korea
Di Ran relative to Shanshan Lin China Shanshan Lin's profile →
Citations per field
00.5×4.5×
Shanshan Lin · 1×
Citations per year

Countries citing papers authored by Di Ran

Since Specialization
Citations

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

Fields of papers citing papers by Di Ran

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

19 of 19 papers shown
#Work
1 201855
2 202055
3 201848
4 201847
5 201719
6 201917
7 201815
8 202311
9 201911
10 20168
11 20167
12 20167
13 20244
14 20241
15 20161
16 20251
17 20251
18 20250
19 20250

About Di Ran

Di Ran is a scholar working on Rheumatology, Statistics and Probability, Surgery, Molecular Biology and Health, Toxicology and Mutagenesis, having authored 19 papers that have together received 308 indexed citations. Recurring topics across this work include Osteoarthritis Treatment and Mechanisms (5 papers), Statistical Methods in Clinical Trials (3 papers), Total Knee Arthroplasty Outcomes (3 papers), Advanced Causal Inference Techniques (2 papers), Health Systems, Economic Evaluations, Quality of Life (2 papers), Trace Elements in Health (2 papers), Statistical Methods and Inference (2 papers) and Heavy Metal Exposure and Toxicity (2 papers). The work is most often cited by research in Rheumatology (53 citations), Health, Toxicology and Mutagenesis (35 citations), Nutrition and Dietetics (27 citations), Molecular Biology (106 citations) and Cancer Research (21 citations). Di Ran has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Erin L. Ashbeck, C. Kent Kwoh, Lingling An, Ernest R. Vina, Zongping Liu, Jianchun Bian, Jianhong Gu, Yi Wang, Xuezhong Liu and Yan Yuan. Their work appears in journals such as Osteoarthritis and Cartilage, Pharmaceutical Statistics, Seminars in Arthritis and Rheumatism, Arthritis Care & Research and Clinical Orthopaedics and Related Research.

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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