Ran Luo

4.5k citations
55 papers · 2.6k · 1 hit paper · h-index 18

Impact in

Papers in

    • Renal Diseases and Glomerulopathies 6
    • Acute Kidney Injury Research 5
    • Chronic Kidney Disease and Diabetes 4

Ran Luo

48 papers receiving 2.5k citations

Hit Papers

Kidney disease is associated with in-hospital death of patients with COVID-19 2020 · 1.8k citations
1.8k0+2+4Years since publication50010001.5k

Peers

Ran Luo
Comparison fields: 5 of 125
  • Infectious Diseases 1.6k
  • Nephrology 530
  • Neurology 659
  • Oncology 646
  • Obstetrics and Gynecology 161
Replace Shuwang Ge with:
Shuwang Ge China
Yichun Cheng China
Mahesh V. Madhavan United States
Daniela Tomasoni Italy
Ismaı̈l Elalamy France
Meghan E. Sise United States
Grigoris Gerotziafas France
Jan M. Griffin United States
K.M. Kant Netherlands
Jennifer Haythe United States
Ran Luo relative to Shuwang Ge China Shuwang Ge's profile →
Citations per field
00.5×1.5×
Shuwang Ge · 1×
Citations per year

Countries citing papers authored by Ran Luo

Since Specialization
Citations

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

Fields of papers citing papers by Ran Luo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Kidney disease is associated with in-hospital death of patients with COVID-19
Hit paper breakdown →
20201826
2 201878
3 202078
4 201871
5 202156
6 201837
7 202230
8 202029
9 202029
10 202325
11 202223
12 202123
13 201822
14 202221
15 201921
16 201819
17 201617
18 201617
19 202214
20 202013

About Ran Luo

Ran Luo is a scholar working on Nephrology, Oncology, Molecular Biology, Radiology, Nuclear Medicine and Imaging and Immunology, having authored 55 papers that have together received 2.6k indexed citations. Recurring topics across this work include MRI in cancer diagnosis (7 papers), Renal Diseases and Glomerulopathies (6 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Acute Kidney Injury Research (5 papers), Chronic Kidney Disease and Diabetes (4 papers), AI in cancer detection (4 papers), COVID-19 Clinical Research Studies (4 papers) and Systemic Lupus Erythematosus Research (4 papers). The work is most often cited by research in Infectious Diseases (1.6k citations), Nephrology (530 citations), Neurology (659 citations), Oncology (646 citations) and Obstetrics and Gynecology (161 citations). Ran Luo has collaborated with scholars based in China, India and Singapore. Frequent co-authors include Shuwang Ge, Gang Xu, Yichun Cheng, Ying Yao, Junhua Li, Lei Dong, Meng Zhang, Kun Wang, Zhixiang Wang and Dengbin Wang. Their work appears in journals such as European Radiology, BMC Nephrology, American Journal of Nephrology, Frontiers in Oncology and Clinical Journal of the American Society of Nephrology.

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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